Live @ YC Demo Day | Garry Tan, Delian Asparouhov, Matteo Franceschetti & More

You're watching TVPN. Today is Wednesday, June 11, 2025. We are live from the palace of Party rounds. Oh, my God. It's YC Demo day. Welcome to our YC Demo day stream.

That is insane.

We have Gary Tan joining us. Wow. You absolutely destroyed my laptop. That is insane. We brought lots of party favors. We brought lots of activities for when we talk to founders who are doing extremely amazing things. If that's going off every time the founder hits a million dollars in ARR or signs term sheet, I think we are going to be up to our necks in conference. We got a lot of confetti. We got some gifts we're going to be giving out. We got some surprise gifts, some hats. We're going to take you all through it. Gary Tan, welcome to the stream.

He is. What's going on?

The president of Y, Commander Gary. Gary Tan. Good to see you. Great to see you.

Great to see you. There's a line around the block still. Is that right?

People are pumped.

Oh, my God. Yeah.

It's absolutely slammed. Take us through. What are you seeing? How's one going? What's actually changed because we're in a different location. Yeah, we're literally break it all down.

In the middle of. This is like our hq. You know, this is. You know, we got the spring batch together. This is the first spring batch that we've ever done.

X25 now.

Yeah, yeah. Paul Graham doesn't like X, so we're slowly replacing it with spring.

Spring. Okay.

There we go. You know, when you create a place like this, I think you get to dictate little things like, you know, not liking X. So, yeah, so we got to write out spring. But, you know, I don't know. What do you think it should be? It could be P maybe. If it's not X, it's pronto.

Do we have to have a mathematical notation for this?

Maybe, yeah.

Like different. You know, we have the Y combinator algorithm. Different algorithm to define the different seasons.

I think. I think just forward, you know, winter, spring, summer, fall. Yeah, well, I mean, the. The energy from the founders is really electric. Honestly, is insane. Like, downstairs we got. Well, the fun thing about hosting all of the investors in our house is that I got a whole whose house? Our house chant downstairs. So, yeah, we got the. Give us an overview of the. We heard a little bit of your talk earlier, but give us kind of a breakdown of how you introduced today. Yeah, absolutely. I mean, dude, it's like 90% AI. It's about 10%, 11% hard tech, which is awesome. And then the really crazy stat is, you know, how the last four batches, about the last year, you know, the batch itself as a whole has been growing revenue by 10%. This time it's 12. There we go. So we're actually inflecting up and that's what you would expect. We're in the middle of the age of intelligence. Six months ago, nine months ago the models were 90 IQ, then they were 110, now they're about 130. We're sort of entering super intelligence zone. Two digit IQ incoming. Yeah, that's right.

I don't even want to talk to that. Yeah, but yeah, probably very valuable.

I thought Sam's essay yesterday was very prescient in that. Like that's, that's sort of the silver lining. Like everyone's sort of worried, you know, what's going to happen to the jobs. Like to me what's going to happen is the exact, I mean it's actually an opening. Right. Like the wild stat that we're seeing is actually the number of 18 to 22 year olds applying to YC and getting in is up 110% year on year. Right, yeah. So, you know, is that driven by.

People liking to drop out of college or skipping college entirely? Is that because they're, they're viewing college as kind of like, I mean there was always a meme about like, oh what, will you put YC in the education section of your LinkedIn?

Yeah, yeah.

Now it's like, oh wait, no, YC could actually be the replacement. Is that intentional?

Well, the extreme meme here that is interesting to think about, like I don't believe this, but you know, the memes among, you know, the 18 to 22 year olds in particular is this might be the last time you can start businesses.

Oh, interesting.

Because you know, once super intelligence hits then you know, the moats that, you know, the businesses that will exist will sort of ensconce like the seven powers of the moats out there.

Sure, sure, sure. And then it'll be maximally efficient.

Yeah, exactly.

They just reach their terminal value immediately and maintain it forever.

So you're trying to get network effects, you're trying to build, we're trying to get brand, you're trying to get a cornered resource. Sure, sure, sure. And then the wildest thing here is that, you know this perfect. Someone was telling me yesterday, right now if you look at college grads, the rate of unemployment for CS grads is actually 2x that of art history majors. I have not looked this up yet. Everybody's been quoting that. We've heard that too.

There might just be something crazy going on with art history majors. They found some hack and they're all getting employed. It's full employment for them. Very interesting. Um, question on the AI side. How are the companies feeling about the current battle between little tech and big tech? We saw with wwdc, it feels like Apple's kind of retreating from some territory. We could be seeing more creating opportunities for developers for, like, mobile apps. We could see another mobile app boom. Because Apple's saying, hey, look, maybe we're not the company to build every single AI experience on the iPhone. We're seeing new hardware maybe come from OpenAI. There's different stuff going on with open source. What's the interplay between the average YC company and the Mag 7 right now?

Oh, I mean, the good thing is we still have. We have net neutrality and that thing. We have seven companies in the mega tech world. But you know what? Like, anyone can just put something on the Internet and they get distribution, Right? So I think that the most important thing right now that I think all of us should really be considering is we need platform neutrality. Right. You know, the second that, you know, today you open your Siri and you don't get to choose, you know, do I want perplexity? Do I want anthropic? Do I want, you know, chatgpt on there? Yeah, you know, no, like, this is actually the next sort of unfolding that needs to happen. We actually need the platforms to allow other people to enter. But if we do that, we can actually have tens of thousands or hundreds of thousands of companies, each of which can get to a billion dollars net revenue each. And, like, you could do it probably with 10 people. Right? So if you link up these two super megatrends, like, that's the future that we want to live, Right? Like, you can be 18 to 22. You don't necessarily have to go in, like, the credential matters a lot less. You know, what matters now? It matters, you know, your agency and your taste.

Yes.

Right. And so. And you don't have to, like, go and get anyone's permission. In the nature of LLMs. You could actually get a better tutor from an LLM than you could from at times working under somebody at some big company who would maybe explain, here's how you make a financial model for a software company, but now you can just talk enough with chatbots that you can probably figure it out even better than having, like, a mentor.

Yeah, I want to Ask about applying to yc. Have you noticed that the apps are becoming more GPT driven? Are people using AI to write their apps? Do you recommend against that? What do you think?

I mean, if anything, like, I think the best apps, you know, in the past we might say, oh, this is AI slop. I think we're. Because the models are now smart enough. Like my writing process for instance, has totally changed at this point. Like I am, you know, you're actually able to come up with better ideas. I think, you know, I would rather, I would rather people actually prompt to get like all of the ideas out there. You know, one of the things I've been using in ChatGPT lately is like, give me 10 options for different concepts or ideas that might fit here. And then what I'm doing is I'm using my, like, I'm using my prompting to do that. And then on the back end it'll give me like 10 things. Five of them make no sense. Two or three of them in my brain, I'm like, oh, I didn't think about that. That actually is a useful thing that I can put in with these other concepts that are in my head.

Yeah.

And so I think it's actually, you know, the computer is a bicycle for the mind. Like if you can prompt really, really well, you know, using it just, I mean, you have to treat it like a vehicle, right? Yeah. It is not a destination of its own. It's actually, you know, this is like the self driving car for the mind.

Yeah.

Right.

I mean even just.

Yeah. Like a co worker, all that matters is the end output. And if you're working on any type of project, not working with a smart collaborator is going to lead to a worse output.

Yeah.

And O3 Pro.

Yeah, condensing down these ideas because I've read a lot of apps where it's like, wow, there's actually like some really incredible KPIs in here. But you buried it in paragraphs of exposition that were completely unnecessary. And I know that the people that are actually reviewing the YC apps are not going to read this far. And so just having it as a copilot seems like a really, really.

How have you and the other group partners pushed to guide the batch around reporting on revenue? Right. There's a lot of conversation around what is ARR? It's sort of this flexible definition. There's obviously a lot of pressure for every founder coming into demo day to show results. How do you guys kind of guide what we'd like people to do is put a Contracted ARR if it is. And then if it has an opt out clause where people can sort of get out, they should just have a little star on it and it's like opt out at 30 days or whatever. This. I think it is very, very important that founders are just don't engage in securities fraud. Kind of a basic thing. Right. So you know, I think that it is a. The amazing thing about the tech today is like the demos are so impressive that people are willing to take a big chance.

Big companies sign up for big deals and yeah, they obviously want some flexibility. But. But being really clear about that, I mean these are non GAAP metrics.

That's right.

You know, there is some gray area, but we need to define new metrics as we move forward.

Are you seeing companies able to pivot more times with within a single batch and just iterate faster output? Because historically it wasn't unreasonable for a company to pivot a few times to get to something great. And maybe they only have two weeks at the end to really sprint and show progress. Now I could imagine certain companies like really, really, really pushing it. Have you seen that at all? Yeah, absolutely. I mean something like 30% of the companies change their idea during the batch and that's actually great.

I mean it means as you're researching and building.

Yeah, and I think that that's always been true. I mean some of the biggest companies end up being, you know, literally pivots from like two, three weeks ago.

Yeah.

And then I think that, you know, people might say, oh, that, you know, that kind of sucks. Or you know, why is that? I mean, I think it's good news. The good news is like, you know, you can just do things.

The good news is when I think of the YC mantras, I think build something people want, talk to your customers, is you can just do things. A third that we're adding. Is that important to have that volition, that agency? It's the distillation of agency, right?

I think so, yeah. I mean a lot of it actually. I think the most important thing that I feel like everyone has to learn the hard way is to learn the sound of your own voice. To say, not to get all bicameral mind about it. Get it? Well, no, I mean if you read PT's old essays, one of the things that really jumps out at me is to what degree? Your childhood, your schooling. He has so many essays about what high school is like, being a nerd. All these things really spoke to me in that the process of becoming actually a founder is actually a journey inward to actually learn the sound of your own voice, that you can make your own way. You. You can have agency just because, I mean, actually, by definition, the startups that create new categories require a level of courage that people have to find within themselves. Actually, you have to say, actually, you know what? I know the Wall Street Journal says that and the hater D sell journalists say this and all this stuff. You have to actually separate yourself from the default view of how the world works. And then you're actually trying to divine secret knowledge by going into the markets, going to talk to people that have never, you know, even touched chatgpt yet. Right. Like, they don't know the. It's like that meme where you're, you know, you're the tech guy, like, in the corner.

Yeah.

And then, like, everyone's dancing and they just don't know. They don't, like, that's where we're at still. Like, it won't be like that for another year or two, but, like, for now, that's still true. You go into any business in the world, they don't know this revolution is about to happen to them and we get to create it.

Yeah, yeah, yeah. Last demo day, we talked to a company that was doing AI voice interactions to help the elderly process Medicare receipts, essentially, and they discovered that the. The elderly were talking to their chat bots for, like, three hours.

Yeah.

And that's just something that, like, you might, you might be able to predict intuitively. But I thought it was just a very, A very funny, like, discovery that only happens from actually trying to build in that. In that market with the latest and greatest technology. And that's what I love about YC Demo day.

What's your latest thinking on batch sizes? Is that. Is that. Are we, Are we staying, you know, where we're at, the high level is like, we want as much prosperity in the world as possible. You know, Brian Chesky is on my board, you know, Paul Graham and Jessica Livingston, Carol Levy. The board has given me my directives. It's, you know, what we need to. This is the tree of prosperity. Let's have the tree of prosperity grow. But, you know, I think that YC fundamentally is the managed marketplace. You look at an Airbnb, I still super interesting. I'm still bullish on Airbnb and that you look at the amount of space in the world, like, the amount of space that has been listed on Airbnb is still a tiny fraction of what it could be. And what does that unlock? And it Unlocks new experiences, travel like a human. Like all these things, you know, $100 billion company from nothing. And I think that the same thing is about to happen to innovation and venture. But we have to do it thoughtfully. Right. Like, you know, we're at demo day here. We have more than a thousand of the top investors in the world all congregated here. Right. We have a thousand people in this building. That's amazing and incredible. You know, we need to grow them thoughtfully, like, we need. You know, what I need is I need YC to continue to provide returns. Right. And, you know, can't comment on, you know, the rumors about scale this week, but, like, we need a lot more things like that and we're getting it. Like, this is sort of uniquely the community where that happens.

Talk to us about the two new partners that were added to the YC part partnership.

Oh, yeah, there's three actually.

Three?

Yeah. Sorry. Yeah. Andrew Micklis and John Shu, actually.

Okay, cool.

Sorry, I almost announced. No, yeah. Tyler too.

Okay.

Yeah, that's Tyler too. I mean, all of them created companies that exited for, you know, hundreds of millions to, you know, pager duty as, you know, a public company. Wow. You know, north of a billion.

That's remarkable.

Those are exactly the kind of partners that we want at yc. It's like they've been there and they've done that.

So roughly how big is the partnership now?

It's 15 partners total.

15 partners, yeah. That's great.

Yeah.

So you can still keep the actual, like, group sizes fairly small within the batch.

I mean, that's the main. You can just basically guess at what the batch size will be because each partner can do 10 to 25 companies, depending on how hard they want to work. But, you know, I don't think it's a numbers game. I think it's, you know, we want to fund all the really, really good founders. And I feel a little bit embarrassed about, you know, we're accepting companies at a 0.8% rate right now.

Wow.

Right. And so, yeah, you know, I think that we're behind the eight ball, actually. Like, you know, I feel really good about this. Like, we're going to keep growing what we got here, but I also need to grow the partnership and then we need to fund better and better companies. And then, you know, this is a 10, 20, 50, 100 year thing. Like, we're trying to build Y Combinator into a multi hundred year institution and we need it. Have you had any companies go through this batch and decide not to raise additional Capital at this point. Point. Because they're just making so much revenue that they have. I mean, famously. Tom funded Axiom. Last batch. Yeah, yeah, yeah. Hundreds of millions of dollars in pure profit. So I saw that and I was, like, trying to look back through our stream and like, did we. I mean, crypto's wild, man. Yeah. Wild west. It's a wild west.

That is insane.

Yeah.

Well, we'll let you get back to it. Thank you so much for coming on the stream.

Thanks for having me. Have fun out there. Thanks.

Great. Well, we will be moving into interviews with founders and VCs who are coming on the the show, who are here at YC Demo day while we bring in the first. Oh, we're ready. Let's do it.

Fantastic. I thought we were gonna be new news. What up? Welcome to the show.

I'm John. Nice to meet you. Nice to meet you. How you doing?

What's going on?

Break it down for us.

How we doing?

Down for us. How's. How's demo day going? Grab a water, introduce yourselves. Introduce your company, please.

All right, Ken, hold up the microphone a little bit, both of you guys.

All right, good. Ken, Cool.

CEO of Kaizen.

Nice.

Michael cto. Okay, you guys pitch like five minutes ago or ten minutes ago. Five minutes ago.

We came right down here.

Spread the word. Yeah. How are the nerves, you guys? Is that like a walk in the park? Yeah, it was fun. It was fun. It was.

You've done it at alumni and then. And then probably like three to five full partnership pitches before, right?

Yes.

Okay.

So I mean, I probably. Yeah, said this a hundred times, a.

Thousand times, almost a few years ago. Well, you got to say it one more time. Give us the high level. You don't have to give us the whole pitch, but break it down.

All right. Kaizen helps developers instantly integrate into websites without APIs. You know, we work with companies across logistics, healthcare, and financial services to integrate to a wide variety of legacy portals.

Very cool. Talk to me about how you're doing that. Is there MCP involved? Are you kind of using AI and LLMs to read the HTML, Kind of reverse engineer an API from the front end? What's going on?

100%. The latter of what you said. Computer use has changed the game. A lot of this stuff, you know, you think about it. Hey, there's a. So such a small subset of software that has APIs that people can integrate with, build products on top of. But now with computer use, computers can do anything.

Cool.

Anything available on the Internet.

And that's what we help Companies Reactions to O3Pro. Have you tested it yet? Is it. Is it improving things or do you build on open source? Like, what do you. Like, what are you excited about in the. In the AI race at the foundation model level?

Yeah, I mean, we love using all of them. We're friends. We're Switzerland, right? Google. Google.

We'll have them all on the show.

You're like, please let the fox in the hen house. Yeah, no, I mean truly, like different models are different for different things. You know, clicking on an item on the page. Like, we like the computer use model for anthropic for that.

Okay, cool.

Like pulling data from a very large table. Gemini.

They come and clutch a little bit bigger context window.

Exactly 100%. I mean, like our approach, we abstract all this away from the end user they don't want to think about. Just happens.

So walk me through some of those use cases. Like, what's the first customer that you've had that has been like, this solved my problem. This is amazing. Walk me through through like a very concrete demo.

One of our most fa. One of our favorite customers to talk about is, you know, they're a voice agent for hotels.

Okay.

So in the Rio, you know, the hotel in Vegas, you know, you call down, you say, hey, I want a burger up to my room. Or I don't know what kind of fancy stuff you all order, but yeah, you'll talk to a voice agent and the voice agent will take your request. Right. And then they'll use. So like calling to get. Like last night we were staying at the Rosewood. Of course. Of course. Surprisingly toothpaste. And we're like, like, it's like it's, you know, you got to. I don't even want to wait, like, you know, I don't know, 20 seconds while it rings and oh, let me transfer you here and all that stuff. You should just be able to pick up toothpaste, please. And it just comes.

Exactly. So how does your service integrate with that experience? Because I know I pick up the phone, I'm talking to a voice agent. I imagine you're using voice APIs to actually mediate that, but then you're designing that. That interaction. Right.

Or rather our customer is traversing. Maybe I want to shout them out. They are a voice agen four hotels.

Okay, great.

And then they use us to write the data back into the property management system, create that service order. So they. A toothpaste goes right up to your room.

Yeah, yeah.

Instead of talking to a person and they're trying to understand you. All this stuff, it just happens instantly. What were you guys doing before this?

We were.

I was head of engineering at a company called trucksmarter. I've worked with small trucking companies my whole career.

Love them.

Great. Big truck guy. Big truck guy.

But lots of experience working with legacy systems.

Web forms. Yeah, exactly. That's where it comes from. Like every shipper in the United States. States. It's a completely different website. I must have written dozens of these. I managed teams. I wrote hundreds.

And probably a lot of web scraping. Exactly. But, you know, now you're on the.

Website and we're building Kaizen so that no one has to do that ever again.

I love it.

There we go.

Talk to us about the metrics. Did you share a headline, number of users, ARR Something to get the investors excited today?

Yeah, I mean, we're in the hundreds of thousands of dollars of ARR. Started working on this. Yeah, let's blow. We got the. We got all the acronyms, all this. The. You know what the A16Z. Like you guys. You guys got term sheets yet? Yes, we're closed.

All right, we have a lead. Boom. The first term sheet of the TV behind waxy demo. Congratulations.

I love this. I love this. Spreading so much debris across this room.

It's terrible. Anyway, thanks for playing along with us, guys.

This is awesome.

Super excited for you. That's awesome. What's next on the build out? How big is the team? I imagine you're raising money. You're going to scale that, or are you building, like, a much smaller team? How are you thinking about that?

Yeah, I mean, this is a massive opportunity, and we're excited to sprint after it. We actually have an employee right now. One. Yeah.

Nice.

Crazy enough to join us during the bag the 500k in the bank account, and we're doing a work trial.

I love it.

Tomorrow we have the money, we got to go spend it, and we're going to build a big business.

Fantastic.

Well, we're rooting for you amazing guys. Congratulations.

Thanks for coming on.

Yeah.

Good luck.

Thank you. My man. Good.

Yeah. See you. Fantastic.

These party poppers are a big problem. Like, it basically was spraying, like, you know, little shards of. Of paper everywhere. But I think it was. We're not gonna stop.

I think as long as it didn't go in my Red Bull, I think we're good. Let's. Let's ideally bring in the next person you want to. Come on. Let's. Let's come on. Okay, we got some people coming into the stream the YC Demo Day Stream 2025. Welcome to the stream. Come on, come on and sit down. You're gonna have to confetti.

What's up?

What's up? Hey, how you doing?

What's going on?

All right.

Hey, congrats. What's happening?

Thank you. So we've emailed or chatted before, right?

Yes, yes. Back in the stack share days. So now people don't know your history, by the way.

They don't.

I. I was talking to a bunch of founders. They were like, what? What?

Yeah, yeah.

He did what?

Crazy around Silicon Valley for over a decade. YC 2012. My batch.

Let's go.

Good times. But this. We're here to talk about your batch. What are you building? Introduce yourselves.

All right, so we are building cursor for DevOps.

Okay.

Basically the challenge right now is you're using Cursor and it's like this futuristic agentic experience.

Right.

And then as soon as you leave the code app, pull the microphone up a little bit. You're back in the past.

Okay.

And so you're dealing with broken CI builds, you're dealing with exceptions, you're dealing with outages, like service outages from pager duty.

Yep.

All of those things are manual.

Yeah.

So what we're doing is we're bringing.

AI agents to all of your developer.

Tools outside of the code editor.

Okay. Walk me through how, how that actually works. Because in Cursor, I'm in the ide. Am I? Am I. Are you puppeteering the AWS dev, you know, like interface, or are you operating at a lower level? What's the actual interfaces of this? Are you rune pilled? Is this like a text? Is the universal interface play? Yeah.

So basically you land on a developer.

Homepage and you see all of your.

Tasks from across those tools. So like exceptions from Sentry, Then you.

See an auto fix button for each of those tasks.

So it's like a priority inbox.

Got it.

Right. That prioritizes everything across those developer tools.

And then gives you one click.

Actions.

Got it. How much of what you're doing requires just building on top of an API for something like PagerDuty, or actually doing a deal with them to integrate at a deeper level, or just puppeteering and computer use. And not even. They're never none the wiser.

So we're actually doing both. So some of the dev tools haven't built out a lot of agentic features, so we're building on top of their API.

Sure, sure, sure.

And then other partners, like one of our first integrations is with Sentry.

Okay.

And we integrate with Sentry AI.

Yeah. Okay, I remember Sentry.

Yeah.

Co founder is actually here. Oh, cool.

Did you guys come in with this idea? Did you have to iterate to it? What did that look like? Yeah, yeah, we did. Yeah, we came in with it. So before this, Daniel, here at Netflix, I was on the team that built the internal developer portal, which was the most used engineering tool at Netflix that helped accelerate the company. You probably heard like they shipped like ads and live streaming and all these things, and that really helped the organization move fast.

Everyone thought that they were going to have partnered with Microsoft and I think they wound up doing it internally because they. So fast. Right, yeah, that's exactly about Netflix. Exactly right.

So it really helped accelerate the team. And that had no AI.

Yeah, no AI in it. Right.

And you can squeeze all that productivity. So then Jonas and I were chatting. We're like, wait, what if we did this developer first? We did it with AI? How productive could you make engineers? You just go from cursor to Star Sling and you're just talking to agents. You're slanging. Slanging bits. How.

What is the go to market motion cursor obviously just goes bottoms up directly to the dev. Is this something that like a DevOps engineer can bring in or do you need to go through a cto, get approval before you do an enterprise deal?

Any developer can actually just sign up to your account and start using it.

The beautiful part is this isn't for DevOps engineers.

This is actually for all the engineers that have to touch those tools.

Sure.

And so it's like pretty much every.

Engineer at the modern software engineering org.

Can just sign up on their own.

Without talking to anyone else in the product. How's the progress? Are you. Are you live? Are you growing? What metrics did you share with the demo day crew today?

Yes. So less than a month ago we launched.

Yes.

And we have over 400 companies that have signed up for the private beta, including Snowflake.

Congratulations. Golden Sacks.

Yeah. So everyone wants agents.

Yes. Yeah.

That's crazy. Where are you guys going from here? Did you. You close around already?

Yes, we have closed. There we go. Yes. Yes. We were happy to give you these. Ramp the money in. Ramp. Yeah. Yes, exactly. Exactly.

Awesome. That's incredible. What's. What's next for the company? You guys hiring, scaling? We're hiring very slowly.

How big is the company right now? It's just the two of you? Just the two of you? Yeah. Literally corporate old school. Yc. Yeah. The way it was. Now there's folks coming through with 25 employees. Yeah, no, no.

We incorporated right after getting into yc.

No way. Awesome.

We were like, all right, the two of us.

That's great.

Build the mvp. What were you doing before, by the way? So I started a company called stackshare.

It was a developer community.

We scaled it to over a million developers.

By the end of the journey, it was used by over 40 million developers. Yeah. And we. I think we did like an interview or something.

It was an interview of the Soylent Tech stack.

Yeah, that's right.

How the hell are you shipping all these calories? And so we talked about all the tools.

Yeah.

So, yeah, it was a big developer.

Community and then sold the company last year. Awesome. Amazing. That's amazing.

You guys are in an incredible position.

Yeah.

Feeling. Feeling really good about this.

Yeah.

You should be confident. It's going to be hard, but I think the confidence should be high. I mean, it's. It's amazing how much we can get done now just with like two people.

Yeah, right.

It's a. Yeah, it's. It's never been done before. So. Yeah, we're excited.

It also feels like an interesting market in that we've seen, like, it's just less monopolistic. It's not like trying to break through a social network where it's like you're either a trillion dollar company or zero. Like, I feel like in DevOps, in enterprise, like, you can understand the roadmap ahead. Chop wood, create a great product and carve out, like a fantastic business. That's why we see so many companies going public every year, so many Decacorns in this category. So congratulations. Thank you.

I'm really sure we keep an eye out for in this batch. Yeah, we're huge.

Yeah. Come on. The next should be watching if you're a founder.

There we go.

Have a great rest of your day.

Thank you, guys. All right.

And we will bring in the next.

Crew stuck for you guys.

Oh, yeah. Bring the phone out of these. Run out of those. How many more do we have? We have a variety of. Oh, I love the sweatshirts. You're owning a color.

There we go.

Ramp owns yellow, you guys. You can have those if you want.

There we go. Feel free. They're limited edition to this demo day.

You can only get them this year.

There we go.

The colors are working together perfectly. Roughly the same saturation. Roughly the same.

On the orange background.

On the orange. Orange paint. Yeah.

Jasper feels kind of vintage. It feels like I've Done it. I've known it. What are you guys?

Break it down.

Oh. We're building an AI agent for bug finding.

Okay.

So right now we have a PR bot. So you make a pull request, we'll take your code, clone it into a sandbox, and then we let an agent just go ham at it.

Okay.

And then we tell you how we break it.

Okay. How much of this is just about speeding up the pace of development versus, like, is there a pen testing angle here? Is that just a complete, completely separate cyber security play?

No, I think we do some pen testing.

Okay.

So it's. We want to basically find any kind of bug.

Yeah.

So a lot of people take like a. A limited. A limited approach at bug finding. So they ever do like coverage testing or they try and find integration bugs.

Yep.

We really want to basically build an agent that can do any of that or kind of what's best for your tool.

Okay, talk.

So you like when people are Vibe coding because are just creating bugs all the time? Keep Vibe coding. Yeah, no, we love Vibe coders.

We.

We're here to help you make better code.

No problems with it whatsoever as long as you buy our software.

Yeah, yeah. You Vibe code, we'll test it. Then you take our output, you put.

It back into cursor, just feed it back in. Talk to me about the. The prompts that you're using to actually have the agent go and hammer it. Like, I imagine that that's not. Just try and find a bug. You've probably gotten very. Don't make mistakes like designing flows.

Vibe code on Vibe.

That goes into that. What goes into actually getting an agent to effectively hunt for bugs.

Yeah. So like, the most important part is just to have like a sandbox where it can like, it can run code, can compile your code, it can. It can run like unit tests.

Yep.

And so then we just get the agent to. Yeah, go ham. And each time that it like runs a small experiment on your code, it learns a little bit more and it's able to do run a better test the next time. So it's able to search a repository, able to run commands to see if you've changes you made actually were propagated through all the files. So we found the bug, which was that someone updated a path but didn't update it everywhere. And so that was these sorts of things. So the agent's able to run these like every. Any command that a person would.

Yeah. Are you doing stuff like trying to stuff multiple variables in a single function, like that type of stuff? Where like there isn't as much fault tolerance built into the code. Maybe they need like a, you know, if else try except clause in there or something like that. Is that the type of like bugs that you're trying to find or is it more about like scalability of code? Like okay, you're making a database call right here. It looks fine now, but if we scale this up when there's and there's a lot of demand, you're going to get cooked.

I think it really depends. So we use the pull request as kind of the initial seed.

Okay.

So what change you make there kind of determines the path that we use for testing.

Sure.

So if you're trying to scale then yeah, we'll, we'll kind of test as if you're trying to scale.

Sure.

But if you're making path changes, we'll test as if you're making path changes. One of the things we find is like vibe coding. Often there's a different flavor of bugs that are, that are happening because of vibe coding.

Okay, interesting.

So they don't. LLMs don't make the same kind of errors that people do because people it with people. Code grows organically elements like one shotting things. So it'll often like forget to add functions. So it's not as easy as pointing to a line and going like this variable is wrong. It's like no, no, you, you like fundamentally missed like this whole section of things you were supposed to implement.

Got it.

So yeah, I think it's okay.

Talk to me about the go to market motion. Is this just a landing page? You're driving traffic to it. People sign up by themselves. Are you doing founder led sales? All the above?

No, no, we're landing page. Like this is our go to market right now. Go sign up. Yeah, you can just go. You install the bot, we have a seven day free trial.

Okay. So it's consumption versus seat based pricing. What are you thinking?

Yeah, it's seat based pricing.

Okay.

So for every developer it's 20 bucks a month.

Okay.

Just simple kind of flat rate.

You running into cost problems? Because we've seen this like you know, the latest and greatest LLM comes out, it's really expensive. GPT03 just dropped by 80%. So anyone who is having a problem with their, with their costs, probably fine right now. But. But how are you thinking about that side?

Yeah, yeah, we found that like actually for just like you know, running lots of experiments on your code to find bugs, that it's actually better just to have a really fast and small model.

Okay.

And so we've actually. Yeah, we haven't had these sorts of problems yet.

What does that mean? Like llama fine tuned. Are you. We've talked to LLM training companies that have trained even smaller models, like just for JSON to, you know, formulation or just translation models or just profanity finding. Are you thinking about going so small you could run it on a gaming gpu or are we still talking about like the big boys?

Yeah. So like right now it's, it's. We've actually gotten like a lot of mileage out of Gemini Flash. We started by, you know, we're. We fine tuned with rl, a model that was specifically good at using tools. And so yeah, we're getting ready to do that. Once we find all our pain points. Exactly. In our current architecture, we can train the exact right thing and the smaller, faster models that are targeted for this specific use case are better. What were you guys doing before yc? We were both researchers, so I was doing research in software testing using large language models. And Matteo was doing his PhD in reinforcement learning. Informal methods.

Very nice. Yeah.

So our kind of research is come together to make this happen. Trouble, trouble.

How are the metrics? How's the rays coming together? How's the pitch for demo day? What are the goals?

Excited about demo day? Goals are raise a lot of money here.

Let's go.

Yeah.

Good luck.

We're going big. Bring some big napkins around. Sharpie napkin. Just do it here. Perfect. And then. Yeah, it's. We're slowly kind of growing. Well, I wouldn't say slowly. We've doubled our growth kind of every. Every week for the past kind of couple weeks.

Nice.

That's a better way to frame it.

There we go.

But yeah, we've gotten. I think we're up to like 18 different kind of companies using our tool.

That's great.

So, yeah, it's been awesome.

Cool. Well, good luck to you.

1800 soon. Yes, 18 after this. When all of you go subscribe. Yeah, then we'll be at 1800. Congratulations. Yeah, it's been a pleasure.

Yeah, we'll talk to you soon.

Show the Crocs off too. Everything.

Let's bring in the next team. How you guys doing? Welcome to the stream.

We got. They've got the shirts. The shirts.

You need one?

I need one.

Thank you. Nice to meet you.

Logan. Nice to meet you guys.

Pleasure.

Tucking your shirts in. We're keeping it respectful company.

What are we building?

So we're code tool. We are building AI agents for security Teams, Cool.

Sorry.

We're building AI agents for security teams. Okay.

Is specifically cybersecurity teams. Are we talking ddos? Are we talking somebody goes in and tries to steal secrets data? What are we talking about?

So like, you know, you can think of. Cybersecurity is split into like AppSec and OpSec, where AppSec's like, you know, defending, you know, the, your deployed software out into the world. And then opsec is like operational security. Right, where it's like, you know, protecting your, your employees from phishing. We're definitely more on the automation side for the opsec side of house. So think of, of like basically like allowing security teams to like triage their tickets a lot faster for like employees. Impossible travel problems or for like, you know.

Oh, impossible travel problems. That's like a, that's like a buzzword for what happens.

Like, you know, Eddie signed in from Singapore. Is that legit or not?

Well, he was in the office earlier today. He couldn't have possibly gotten there because hypersonic travel doesn't exist. Exactly.

Not quite yet.

But that's gonna make it really complicated when you can get from LA to Tokyo in two hours. Everyone's like, well, I guess he did log in to Tokyo. No going for sushi.

It's funny because I think like a lot of people have like this like hacker aesthetic in their mind when they think of cybersecurity, which is like a lot of like, you know, in the movies fucking around on a terminal or something like that. And it's just like when in reality it's like most of the time it's like people triaging tickets day in and day out, that kind of thing. So like our goal is basically to like automate a lot of the BS that these teams have to go through and like a lot of like the annoying stuff and then like allow them.

To get back to work. So what's the go to market motion? Are you doing enterprise deals, Founder led sales, selling to other YC companies? What's the scale of company that needs.

To use Our first customer is Ramp.

No way.

Let's go, baby.

That's hilarious.

I mean, where. I mean, that's tough. You're kind of starting that time is money. Save both. Come on. There we go. I mean, Eric Ramp is just an incredible CEO.

YC alum.

But the motion is we really want to embed with this like the most cutting edge, like the best team, teams like Ramp that can actually inform us as much as we're helping them on how the best teams operate. And so we're looking for like sort of tech forward. Enterprise totally is like, would be awesome. But you know, anyone that's like, you know, pushing the boundaries of what's, you know, possible automation.

Okay, and what does the integration point look like? Is it, is it a single, you know, security person at a company can get set up or is it something that needs to be deployed throughout the enterprise and has a much more, more like staged rollout?

Yeah, I think basically where it is ideally what we would have is we probably first start working with your detection and response team and get that team plugged in. Basically we're heavily leveraging AI tool calling. So the idea is we plug into all the different points in your slack, think like Okta, think like Panther, think all of these different products kind of thing and basically then what we're able to do is deploy out and allow these teams to write their own agents. So they're in there customizing their own system prompts, all this kind of stuff to go out and like tackle their tasks day to day. So I think the initial go to market motion is work with these high tech teams who are really used to automating already and then basically kind of like build up a nice collection of agents, kind of start getting a good network effect, IKEA effect where like people are like building their own agents, sharing them out into the world and then from there we can kind of like move out to wider and wider and like less technical teams where it's basically like we can kind of like start to plug into people's stacks and like wholesale automate out of the gate and like solve a lot of things, these problems. How did, how did you two meet? So we grew up together in Santa Barbara, California. We, we have, you know, lived together for, since, you know, we went to school. But yeah, our third co founder is just outside. He's, he's, he's probably watching us right now, but.

Great.

But yeah, we, we were really stoked when you guys watched our, our launch video.

Oh yeah.

For the. We did on the show.

You guys are that company. That was incredible.

Single best ad I've seen seen this year.

100.

Because, because there's so many ways to do that and have it be just bad.

Oh yeah. It could have been that a million.

Ways, but it was extreme. It was tasteful, it was funny.

It was funny.

It was perfectly timed.

Yeah, it didn't, it just made it funny.

Where did that, where did that come from? Well, so it's funny. We were scared it was gonna flop, to be honest. I mean like, we didn't know how it land, and we're happy with how it did. But no, I. We. We came with the idea. We worked with, like, one of my friends growing up does comedy in la, and I live in la. But, like, she knew a director who, like, was, like, amazing, and his friends, who are also, like, actors and stuff, got in and acted for us. And so it's like it all came.

Together with friends and friends, and it looked incredibly polished. Can you give us an order of magnitude on the budget for that thing?

It was. It was. It was, let's see, five digits.

Five digits, but not six.

Extremely low, Extremely low. Five digits. We were able to work.

It looked like a. It looked like $100,000 project, but it was actually.

It was actually pretty funny. We. We showed. The original idea came from Gary, actually. We showed him the demo on the first week of. And he's just like. We start, like, showing him how you can, like, query slack and that kind of stuff. He's like, oh, you guys got to do the repling thing.

And we're like, oh, my God, we.

Got to do the replic thing. And then we showed him, like, the final cut, like, the night before we went with it. He's like, you guys should tweak these. These couple of things, like, okay, editing and stuff like that.

But it was. It was.

It was funny.

It's funny because it's like YC on YC on YC violence. But it's really just like, look like they're going to sort their thing out. You guys are just having fun.

Did that ad catalyze around for you guys? It did in some ways.

Yeah. Yeah, yeah.

I think we. Yeah, I think a ton of investor inbound off that. Yeah, exactly.

Yeah. No, no, it makes it. It really grounds it because it, like, not everyone works in cybersecurity every day. It can be a little abstract. There we go.

There we go, boys.

Let's go. What do you do with that? You push it up or something?

Yeah, we're figuring out we got a lot of these.

Congratulations.

Exactly. No, it's. I'm super excited.

I think we got to give him a different hat for this. I mean, it's the best.

Oh, man.

Yeah, we can give you two of these. Congratulations.

Really great chat with you guys.

Yeah, great chat.

Super excited for you.

Yeah, we'll talk to you soon.

Cheers.

That was fantastic. I'm so glad we got to talk to those guys. That was such a good year. Out of the year, out of the.

Year, out of the year.

Right. And right at the perfect time because we, we were just hitting like peak vibreal. Right.

And then even a month later.

Welcome to the stream. I'm John. Nice to meet you. Nice to meet you. I'm John. How you doing?

Or die. Season too soon. They. Everyone died.

Everyone died. You didn't hear the story about PMF or die. They died.

They died. It happens sometimes.

Never, never lock yourself in a room for the 90 days. San Francisco DO YC. That's my recommendation. Basically the same from here on out. Anyway, please introduce yourselves and the company.

Yeah, I'm Tom. You guys, look, you're not related at all, right? We're not related. You could go by brothers. People ask us, people ask us.

What does the company do?

We're doing agentic people search. So we have a database, people database of around 200 million people and Interesting. We use agentic search to search over that for companies and businesses to do like sales recruiting, gtm.

So, so are we talking about specifically like I am a recruiter and I need a salesperson and I'm going to go to you to try and hire them.

No, no. So basically like you can put in a criteria. Like essentially what we do is hold, hold the microphone up.

They're here. Push the microphone a little closer.

Essentially what we do is we like, like, like deploy an LLM and assign every profile to that LLM. And then given your criteria that could be like one paragraph long. We would just ask the LLM if this profile like meets that criteria. And then, and then we built like a load distributor to run like 10,000 LM calls in parallel. Wow. Do that at scale. You know, we can, we can search over like 5 million profiles in like 30 minutes.

Okay, so, so walk me through one of the key examples. I'm sure this is live. You have customers.

Yeah.

What's an example of someone using, using this.

So for example, you know, we had a courier come in yesterday. Actually it was just like every founder that was acquired that was a CTO of their startup was acquired by Databricks or Snowflake in the last three years and they still work there. And there's only probably like 25 people in the world that fits that profile. And we found all 25 of them just by using. Because we can use and have an element going just like, because we have like we can throw as much compute at the problem as we want. And then the LLMs get better the more confused you're out. It's interesting to be able to find. You're able to Find information that is historically effectively impossible to find without doing all the work that you guys did.

Yeah, yeah.

Ahead of time.

Makes no sense. So who's who? What buyer or what buyer archetype within an enterprise or business is most excited to buy your product?

Yeah, I mean like mega recruiters, by far.

Recruiting firms.

Yeah, no, just like people that you.

Know, or like a big recruiter at.

Mean, we work with right now, for example. Okay, cool. So you know, like, like just like people hunting for talent, but it's like a generalized type skill. Right. So for example, you know, like in AI labs, training a new voice model and they need like people that speak Cantonese.

Sure.

Then it's like, okay, I find me every Cantonese speaker in the US that has like a podcast presence. Yeah, like, okay, great. These guys can come train our voice models.

Right.

Like that's kind of.

Or they might even need someone who speaks Cantonese and also is an expert in biology.

Yeah.

So they can talk about the biology terms. And that's something that. How are you going to search?

So it's so funny because I, you. I run these type of queries in my own head where we need a videographer who's in LA that has experience in film, but you know, I mean.

It'S also part of teapot. That's basically what we need, has a sense of humor. How would you even know that? Well, if you look through their post.

Basically like as close as you can. If you just give like a criteria to human recruiter.

Totally.

So, so you can imagine like 5000 human recruiters like manually looking over profiles.

And then you know, okay, business model. Are you. Most recruiting firms, they charge on like a per fee basis $30,000 to place an engineer somewhere. Are you doing like a seat based pricing? Consumption based pricing. This sounds expensive. If you're Talking about running 20 million LLM queries at the same time.

It's actually not as expensive as people think because, you know, open source models gotten so good. Okay, yeah, like, like I'm guessing like, you know, any like deep research query costs like $10 maybe.

Okay.

But then you know, like we, we recharge for conversion with, with our B2B.A conversion.

Okay, we recharge by conversion, so that's probably pretty expensive.

And also we have like a platform just that's just available to everybody so they can pay us a subscription fee, search as much as they want.

Very cool.

Do email enrichment phone number.

I feel like we could use this. We might be.

Yeah, we need a guest that doesn't hate tech, that can Talk about this. How did you two meet? What were you doing before yc? Yeah, so we met in elementary school, actually. So we were originally from Canada.

Let's go.

We went in elementary school and we became close friends. Yeah, it's been great here. But we became close friends when Eric, he uninstalled windows on my computer. And I was really pissed at him for a day. And then we fixed it. So then we became great friends after that.

Couldn't load anything.

I had homework. It was during school.

And then ultimate prank, uninstall windows on your best friend's computer.

Boys being boys. And then we spent one semester at college each. So I was at Penn, he was at UC San Diego. And then. And then come January, we were both like. Like, why are we even there?

Let's drop out. 18.

19. We're both 18 right now. Let's go.

Here we go.

Yeah. What's. What's the youngest team that you've met here besides yourself? 17 there is. 17 there is a high school senior.

Okay.

I met when I. Dinner, dude. Okay. Yeah. I'm doing some robotics. It is getting younger. Yeah, yeah, yeah. We have a bottle of wine here. We're going to give it to you. We received one from. Hopefully you're not going back through YC in three years. Hopefully you're at the NASDAQ or something.

Talk to me about traction metrics. Anything that you're sharing here at demo day. Anything to get the venture capitalists exciting.

270 paying customers. First version of the. So I don't know if you guys heard about Linked.

Linked. No.

So, so, so, so a very early version of this product we launched, which is like Rank Stanford. Like, like, like, like Stanford Rank.

Okay.

Which was. So we basically built this. We basically scraped the entire alumni database of Stanford.

I'm sure they love that.

Yeah, they were okay with it. We. We put it online. And then, and then, and then, and then we had this. We had. We had this app where people. People can like see two random alumni and then next to each other.

And then you vote for that, basically.

And then you vote for who's more cracked.

Who's more cracked.

Who's more cracked. And that version of the app picked up like 80,000 users, was how we got into YC and stuff.

Very cool. Very cool. And then.

Yeah. And then, you know, we came down here. 270 paying customers, about 16,000. My monthly current revenue.

That's great.

Since profitable.

Yeah.

No.

Yeah. Wow. Is it just you too, right now?

So there's three of us Three of you? We were two converters, founding engineers from high school. He just graduated. Yeah, we all went to the same high school.

That's amazing.

No, I'm super excited for you guys.

Congratulations on West.

We're going to get a new product and I actually have a bunch of people to send this to.

Yeah, this is fantastic.

You should give it a try. Thank you so much. Yeah, we'll talk to you soon, guys. Great meeting you guys.

Fantastic. Let's bring in the next team if we have one. Come on down. How you doing, Aaron?

What's up? So this is a. Y.C. alumni just raised a Series A today.

Congratulations.

Yeah, so we were trying to make this happen for the last week.

Amazing.

But he just announced his series A today. 17 million, right? 17 million.

Congratulations.

There we go.

I mean, we have stuff to celebrate.

I already got the hat.

Yeah, I got the hat.

Hey.

Congratulations.

Seems like you've done that a couple times.

Yeah, yeah, yeah, yeah.

This is the biggest round of the day.

Who did the round? How far along are you? How big is the company? Give me some stats.

Yeah, yeah. Okay. So 8.8VC did the. By the way, guys, this is awesome. I did like the interview with Venture Beat and this. I'm way more star struck by this. So, like, I'm not just saying that, but I'm. Yeah. So 8 VC led the round. Let's go. Let's go.

Absolute dog.

What. What partner are you working with? Jack Moshkovitz. He's great. He is fantastic. Yeah, yeah. So how far along so we are. And were you in the last batch? No, we were. We were a couple batches ago. We're Summer 23.

Cool.

Great vintage.

Was that still remote or was that back?

No, we were the first back. We were. Yeah.

There you go.

We had an advantage.

Very nice.

But yeah. So Outset does AI moderated research. Okay, so what does that mean? It's like when. When big companies have to do a ton of research, like Nestle has to go figure out what, you know, whether they should launch this weird version of digiorno pizza or something, they go do research. So either they're running massive surveys and they're getting like very low fidelity data. They really know much, it's just a bunch of numbers. Or they're running interviews and that's where it's a one on one interview with everybody. Right. Which is not actually cost effective, so. Totally. So now you can run AI led interviews. AI is leading the conversation, digging in, following up, probing deeper, and synthesizing all that for you.

Got it.

How big is that? How big is the legacy market? So, so the research market is like 140 billion. It's actually a really big one. Yeah, just like, yeah, there's like huge companies that you probably may have never heard, like Ipsos and Kantar and these like big guys that are just kind of sitting there. So. So there's a lot of opportunity. And yeah, we work with like Microsoft, Nestle Weight Watchers who've been super enterprise focused. And yeah, we're a couple of years in.

What are the interaction patterns that you like or you think are kind ofUnlocked by AI? I imagine that voice phone calls is top of mind versus like forms, which was always like available and already computerized, essentially.

It's actually, I think the, the cooler thing is what you can get from participants and synthesize. So it's like, so now we do video interviews and they do audio and they can even share their screen. Right. So all of that is being ingested. And then like people ask like to say, I have an avatar when it's interviewing. And we actually did research and people don't want that.

They don't want the avatar?

No, they don't want the avatar. The avatar is something like weird uncanny valley. And you're just like, people are used to phone calls. Yeah, people used to phone calls and they're fine sharing their video. But like if you suddenly see an AI, you're like, I'm trying to make, you know, 15 bucks doing some research.

Totally.

You suddenly see that you're gonna be all weirded out. So it's actually much better to have AI come through with voice and text.

Yep. Talk to me about recruiting. You said 15 bucks. That's enough to get someone to jump on. But how do they even find out that 15 bucks is on the table?

Yeah, so we partner with a number of different, like companies that do nothing but panels. Like nothing but recruiting. Nothing but recruiting. So you have like user interviews. Prolific.

They probably get some demographics and some basics.

They get all that and they have millions of people that are like ready to. It's like gig work. Right. And so they, okay, I need 100,000.

People that drink energy drinks to give me feedback.

Exactly, exactly. Yeah. You can do all that through our platform. Is there a certain unlock when an AI doesn't need to, like, you know, if a human is scheduling research calls, you know, you can imagine they do like four 30 minute blocks and then they take a little break and they do some more or something like that. I don't know how it works, but An AI could hypothetically talk for hours and hours and hours and hours, like, kind of 100%. So there's like, you know, I think a lot of AI stuff is like, oh, where can it replace the human thing? And now it's cheaper. But actually, like, this. This is taking on the stuff that, like, humans can't physically do. We only have 24 hours in a day. And so it happens that people use it to, like, interview 500 people. Right. In a day or two. And that's, like, it's literally not possible. It's like, just the laws of physics don't allow it. Yeah. And so they're able to do that. They can do multilingual. They kind of do it all at once. So you can wind up, like, unlocking actual, like, stuff you've never heard. Can I curse on this?

We usually don't, but.

All right. Stuff that they would not have uncovered anywhere else.

Yeah, yeah.

And they actually are able to get that. Got it in this way.

Yeah.

What's your. What's your stack under the hood? What models are you using the most value out of? Yeah, we're using a combination. So it's, you know, it's like we're hitting multiple models constantly. But Azure, we're using a lot of Azure, actually, to OpenAI models under the hood to Azure.

Yeah. And it's your model router. Helpful. I saw they announced that at build. I haven't talked to anyone that's actually used it.

I don't know yet, actually. So I don't think we're just rolling it out. So basically, like, what we need is just an incredible amount of reliability because what we'll have is, like, three customers are all running, like, 500 simultaneous interviews. Sure, sure. So we have to actually scale very, very quickly. And also, like, a lot of our customers, like, the nesting of the world, like, they care a lot about, like, super safe, super reliable. So we kind of, like, wind up needing the kind of Azure.

Yeah. And then you're also probably going through, like, peak LLM usage hours because you're not doing in the middle of the night.

No, no. We can't just process it on our own time. It, like, has to happen in that moment. But then we also fall back to open AI. We use Gemini for stuff. So we're, like, hitting a lot.

Yeah. Talk about the. The. Is the voice modality beyond the uncanny valley at this point. Is that why voice is valuable? Are used using voice a lot? Because you can imagine that this might have been possible via text interactions. You're texting your responses back and forth probably get more out of a voice interaction. Are we just. If we talk to you again in like two years, do you think it'll be like, okay, yeah. Now I'm a believer in the, in the avatar thing because it is photoreal.

Okay, so two things. So one, right now what matters most is obviously the modality of the participant. Like if you think about like all we care about is the most deep, like, like thoughtful, in depth data that we can like pull from you that responds. Yeah, that matters.

And that's way better than text and.

That'S way better than our first product.

That we gotta get him talking.

Yeah. Our first like pilot with Weight watchers back in 2023 was like all text and it was actually pretty good. But like it's nothing compared to what people actually say. Sure, sure, sure. And so that's what matters most is like video screen share voice from the participants from AI. Yeah, like so we use voice a lot. So there's a voice to voice mode where there's like no buttons. It's just conversation. And like people like it but like not as much. And I think there's still just, if it's not a person, then it's still got this, the minor imperfections, the kind of slight bits of latency. And so I do think in two years we'll talk more about that. But ultimately like people know it's a computer. Like they know it's AI and like they're kind of cool about it. Like we, we've done a bunch of this research. We're like, do you care that it's AI? They're like, no, like I, I get it.

Yeah, right.

In fact, they like have even expressed that like they'll share more because there isn't a person.

Sure, sure.

It's an idea of like social desirability bias. You're like, I don't want to come off as a person that is X, Y and Z to another human.

I will just tell you, look, I want this to be faster or I want this to taste better. Like, yeah, yeah.

Or like, or like the real reason I'm not using your product is this. I'm not going to say that to a PM or a researcher who's like, yeah, right. But instead you'll tell the real truth.

Yeah, yeah.

And that was like our initial pilot with Weight Watchers was all about weight loss and like that was like a thing people don't want to share a lot about. But with AI they like shared everything about their lifestyle.

Yeah. I mean, it sounds like you've done like you've worked with really big companies and that's where the money is. But when you went through YC or if you're here, you know, there's a big theme of talk to your customers.

Yeah.

Has there been any pull at the lower end of the market?

Yeah. It's funny, I. Sometimes you get a founder reaching out. Like, I really want to use this because I don't want to talk to my customers.

Yeah, talk to your customers.

We don't want you as customer intelligence. Yeah. There's basically like, I think a good, a good reason not to use an AI moderator is like if you could sell to that person.

Exactly.

Probably don't outsource that. Right. Like maybe to build the relationship yourself. So the truth is, especially all the B2B stuff, there's not as much like we usually turn around and say, come back. When you're like a couple hundred people and like you're kind of scaling that out. But yeah, with, with some consumer stuff where you really have millions of people you're trying to learn from, it can make a ton of sense.

Talk to me about the like, data processing and the intelligibility that goes into. Once you have all that data, it's very nice to be like, hey, we have like, you know, 5,000 hours of video.

We repaired a 200 page report.

Yeah. But nobody reads that. So how are you thinking about actually compressing that down? Because that seems uniquely suitable for AI, but there's still a lot of art in terms of like, a lot of people say, oh yeah, I did a deep research report. And then I. The next query was give me 10 bullet points about that because I didn't actually want the full report.

Yeah. Yeah. So, all right, so our vision here is like, we should be building, we are building the like deep research, but for primary research. So you think about deep research, like, all right, all desk research now, commodity. So what if you just ask a question, you just want to like learn from real people. That's much more up to date that whatever, like your own proprietary data. It should be the same kind of idea. Right. End to end agents are doing that. But today, like the premise of AI kind of scaling your qualitative research is that you also have to help them do something with all that conversational data. Right. Because otherwise you're like left with just like hours and hours of transcripts. I'm like, I'm not going to review that.

Yeah.

The application of this is. I know this is not what you're focusing on. But if I was a VC that wanted to write a multi hundred million dollar growth check being able to like get live interviews with like 500 customers.

I mean people are doing this GOG and.

Yeah, that's right. No, this is a huge opportunity actually. So. So yeah, I have a whole side thought. Like I think one of the challenges there is with the expert networks is all about finding the right people. But if you're in a situation where you can find the right people and you can find 100 of the right people. Well, we just had Plato AI on. You should talk to them. They're in this batch. They do like LLM based people search. So you can find like every person that at Databricks that was a former founder. No, there's an opportunity to connect all of that through that. But what I was going to say with the synthesis is what we do is basically taking all the videos stuff and then we like process it and we give you basically reports. But it's like not just a, like here's what it's telling you. Like deep research style boy you could do is like start like slicing and dicing it. You could like we quantify it, we give you breakdowns, we like build highlight reels for you and then like people can like cut it and segment it and so it's like a whole analytics suite. Yeah. On top of qualitative data which is like not a thing that has ever been done. Yeah.

Because what were you doing?

What were you doing before this? So before this I was a VP of product at Triplebyte, if you know. Yeah, Harsh hired me. Yeah, exactly, exactly. He, yeah, he. Anyway, so, so I worked at Triple Byte at Jumpstart, another company. So I was like leading product and design teams. But earlier in my career I was like a, I was a consultant where I was doing like this work non stop where I was like, are you, are you a nominative determinism guy?

Yeah. Yeah. You're an absolute canon to fire a billion dollars into research.

I, I have not capitalized on. I was looking at we're big, we're big, we're big.

Into the names or the truth? The names.

I like that. I like that. I have a friend who always calls me the loose cannon. You can never know what to expect cannon.

That's a little bit too much. Dial it in the capital cannon. You can trust it with your capital. Just give it to him. Fire it in the capital cannon and boom.

Yeah, I'm gonna pivot off of loose cannon onto Capital Canon. Yeah.

Aaron, Capital Cannon. There you go. Anyway, this has been fantastic. Thanks so much.

We'll have you back on sometime. Yeah.

Seventeen million dollar Series A.

Let's go.

Fantastic. Biggest round we've heard yet. Let's bring in the next guest operative.

There we go.

Welcome to the stream. How you doing?

How's it going?

Good to meet you. I'm John. Eric. Nice to meet you guys. Good to meet you. You're going to want to keep those mics close to you because it's NOISY here at YC Demo Day 2025. Good to meet you. Can you introduce special operatives and the company that. You're awesome.

Yeah, we're, we're operative. I'm, I'm Chris and Chris Settles. This is my co founder, Eric Quintanilla.

Very nice.

You can introduce yourself as well. But we're, we're friends from high school. We met at West Aurora High School School in aurora, Illinois in 2014. We were doing our first Java programming class together and 10 years later, here we are. Deep, deep. What. What did you guys do between then and now?

Yeah, do you want to learn other programming languages?

Do you want to tell more of the story, Eric? Yeah, I mean we went to college.

Maybe you still write Java? I don't know.

Yeah, we went to college, worked at a couple big tech companies, worked at startups. That's here.

Amazing rip.

Chris was at Uber. You can talk about that.

There we go.

Nice. Did you wear the pit vipers during your, your main pitch? Sorry? Oh, you're asking where the sun. Did you wear them while you were pitching the.

The phone?

Oh, no, I just got these from Marco. I don't know. We saw Marco in here wearing these.

We're like, marco, you look so cool. So break down the company.

Yeah. What are you guys doing? All right, so we're working on web app code generation for internal APIs. So you can imagine having like a.

Lovable plus a retool for your company.

Where you can on demand just create any kind of application that you're thinking about, whether it's like a new dashboard or it's some kind of like app to manage your airflow.

And you want to have a nice.

UI with it and you want to connect it to all these different pipelines. I mean that's just one use case you can think about, but you can build any kind of front end application that connects to existing APIs that you have in your company.

Yeah, I remember like when you, when you said set up like a Django website, you kind of get like the Django admin, like out of the box and you can just investigate all the different classes that you've kind of defined in the database. What are some examples you could give us of these internal APIs that typically float around in companies? Or you can either give like a precise example or just a general example. Yeah.

Do you want to give one? Yeah. I mean, a lot of the use cases are centered around, like, customer service. So people, like, want to interact with like a database. Sure. Who are doing support, want to, want to like, change, like payments and stuff like that. Data visualization, stuff like that.

Okay. So yeah, I mean, is it unique about like, bringing different services together? Because a lot of, like, smaller companies would say, you want to, you want to look at the payments admin, head over to your Stripe dashboard. Stripes already built that. Where, where are. Where companies currently falling short. Is it that they're. They're not bringing the data together across services, or is it that they're developing like, like their own databases and their own, their own tables that just don't have a. Don't have an API out of the box or don't have a. Don't have a web app in front of their API out of the box?

Yeah. Yeah. So as. So definitely startups is super easy to just say, okay, yeah, check out the Stripe dashboard. Manage. Then that's what Stripe does.

Typical customer service flow. Like, you go to Shopify for this and then you go to the CMS for this, then you go to Stripe if there's a problem over there. And then you got all SaaS products.

Yeah, but one of the things we noticed, especially at our jobs in big tech, is that eventually your product gets really complicated and you actually don't. There's not a SaaS product that those services offer. And so you end up needing to build something on top of it in order to manage it. And then you end up building. Needing to build all these different internal tools to like, have all that organized in a nice way where you can connect it all together. Because the traditional SaaS doesn't support the features that you're looking for.

Got it.

And so then as a result, you hire a team to build out those kinds of applications and then spend a lot of money. And that's what we're trying to bridge that. What was the aha moment for you guys? Were you seeing the kind of explosion of tools like lovable and things like that? And then, and then you saw, wait, why aren't people doing this internally? Or what was the kind of moment that you guys decided to focus on this. Yeah, I mean, I think for us we saw like, we launched this like lovable type product and we saw a lot of people from companies using it as a consumer product actually at first. Yeah. To build internal tools for their company. So we actually, we were like, oh, we should just bring this directly. B2B. Cool.

Very cool.

Yeah. In some ways it makes sense. Being able to like quickly generate something, test it and then like it's very different than sort of these like ephemeral products that exist and ultimately will need to be, I don't know, sometimes completely rebuilt.

Yeah. Talk about the go to market motion. It sounds like this is not a company where you need to sell to every other startup in yc. Who are you selling to? How are you actually convincing them to take the leap and go with you?

Yeah, so we're starting from the initial sort of traction we saw with the consumer product. We decided we want to work on this enterprise direction and, or like larger organization direction because of these use cases we saw with people signing up for all of their work emails and building apps. So we're starting some design partnerships with large organizations. I can't say, I won't say the exact name. And we're planning to kind of just leverage our warm intro outbound network, Warm Intro network to be able to talk to some more organizations. And I think like there's some, there's actually a large percentage of companies that even will try to use like Retool to build internal apps. And so we like, we think we can work with some of the other YC companies that are doing things like that, using that. But maybe.

Have you guys worked with Retool Demo day?

Are you guys, are you guys working with Retool or you, you, you kind of, kind of competing.

Good luck. But good luck. We have, it's a big market.

Yeah, we have a pretty cool direction that's like pretty unique at the moment.

So we're excited about. Talk to me about the actual instantiation of the web app. I'm sure you're using AI and co generation. What's working? What. How much is. Are you leveraging O3 or Claude or open source or Gemini? What's. What are you looking for? Where are the models falling short? Where are you kind of like trying to stay ahead of the puck because everything's developing so quickly you want to take it.

Yeah. So I think on the platform, I think the foundation models provide like a nice foundation.

Yeah.

But like we try to leverage good tools. So like viewing the File tree. We had a browser agent on top to test and validate the app.

Okay.

The model's far short in. I think they're good at like going 0 to 1, but I think like, if you go 0 to 1 and then there's a bug going back and finding what file it is, what's implicated in it, I think it's very hard for the models and it's better to just start over.

Okay. Yeah. Have you benchmarked against how long it takes someone to build a web app for a on top of a private API using Cursor and just saying I'm gonna vibe code this myself versus your product because it feels like it's getting faster and faster and there's a lot of. I mean there's like, there's whole, there's whole open source projects for like build out the API docs around an API just from, you know, this was programmatic. This wasn't even, this wasn't even AI. You know, you just have like, oh, you want to, you want to put the. You want to instantiate this as a blog. Okay, here you go. Yeah. What are you benchmarking against?

Actually, maybe a cool story on the backstory of how we came across this is that we actually started with people wanting to develop apps inside Cursor. So one of the kind of unique insights we had is that today developing any kind of front end requires that you ask Cursor for a prompt and then you open up the webpage and go click on it and just verify that it looks how you want it to. You can go and then tell Cursor, okay, I want to move the blue button inside the black box. And you have to just keep prompting it until it does that. So actually one thing Eric and I worked. The first thing Eric and I worked on was actually an MCP tool that allows people to opens up a browser agent that can go and view changes that a coding agent makes. And it will just test to see if the visually, if the app actually works. Actually, there's one of our users over there, he's just giving us feedback on it and we grew that to around 1000 GitHub stars. And so people got really excited about that. But we wanted to bring those same tools into a product like Lovable or like codegen and be able to have all of this code generation with testing built in. So that way we can allow users to just go from prompt to a working web page without any interaction.

Very cool.

Are you guys still raising right now? We're still raising. We've been back by Weekend fund and also a few other angel investors, and we're still raising and open to chatting with other investors. We have an angel investor and Retool invested in us.

Play the hits.

Play the hits.

Play the hits.

Find something you love. And just.

Did you have any metrics that you. That you shared here at demo day?

Yeah, as I mentioned, we had the GitHub repo. We, like, scaled to 100 or, sorry, 1,000 stars.

That's pretty good. Yeah.

We just launched the consumer product we had. It got around 2,500 different users using Operatives.

Yeah, that's great.

And right now there's, like, about a 4% conversion from free to pro plan. We have a pretty generous free tier, so you can go and use the app however much you want. But for the power users, there's around 4% of them converting. So we have about 1.5k monthly revenue at the moment.

Amazing.

And that's with the consumer product, but we're planning to scale more. More revenue. I think the enterprise. You could probably get that on your first contract. Exactly.

Thank you for stopping by. Please.

Congratulations, guys. Thank you so much. Have fun out there. It's great having you on. Thanks.

We'll talk to you soon. All right, let's bring in the next crew. We are at YC Demo day. Hey, how you doing?

What's up? Time to talk sleep scores.

Let's talk sleep scores.

How did you sleep last night?

It was brutal.

I was.

I was at the Rosewood.

The Rosewood doesn't have eight sleeves. This is a problem. Yeah. Yeah. 90% of the guests are. Good to see you.

Yeah. I want to talk F1. I want to talk F1. You just did an interview with Charlotte Claire. Yeah. Break it down. What did you learn from him?

His obsession for every single detail in his preparation.

He goes for two weeks at the mountain in January to prepare for the.

Season, and that's after elevation.

Elevation, Training.

Elevation.

And then he does every sort of skiing for like, eight hours a day. And then he goes to the gym and then he brings the pod. He sleeps on the pod while he's there.

That is when he really prepares the season.

And then his obsession for every single detail when he travels. All the gadgets that he brings with.

Himself from Devices for recovery.

Sure. Ice bath, obviously. The pod. Yeah.

The neck training.

Is he doing the leg compression thing? That's a big one right now. And I don't know if you saw it. So we. So Charles was talking to us about the fact that when he's on the Grid is really hot. Yeah, yeah. And a lot of athletes in Formula one now, they use this vest, cooling vest. Oh, interesting. But they don't really work. Okay.

And so the way you want to.

Really cool your body, you need to cool the palm of your hands. Oh.

And so I was with my co.

Founder, Max, and we said, what if we build cooling gloves for you?

He said, oh, that would be interesting. So we built the gloves in three days.

No.

No way.

And then one of us, one of our people, they flew to meet him in Barsa. In Barsa, they were like 35 degrees Celsius.

It was super hot.

And so Charles started using these gloves, cooling gloves that we built for him. And then as he goes in the.

Box, Ferrari takes a picture of him.

Just no, for Scuderia Ferrari, blah, blah. And so he was on the COVID of the Instagram account with his le. So it was free branding for us.

With the device we built for him.

So you see that with the tires, they have the tire warmers. Then you have the hand coolers. Every different part of the F1 machine needs to be temperature controlled. So him using these.

And so Padel players, tennis players, they.

All say, oh, can I use it? And say, but, man, we did. We did a one off. And so now we have a team that is building this cooling gloves for a few athletes. That's. That's incredible.

Great partnership.

What has YC demo day been like for you? Are you here just trying to sell eight sleeps or are you also doing some investing? What are you. What are you getting out of YC demo day today? Yeah, yeah, I do a bunch of investing. I invest in. Tested like, probably 20 companies in this batch already.

Wow. You gotta get. Yeah, you gotta get them in here.

You need to start early or then you're out. Oh, yeah, you gotta get in early. You gotta get in early. And so in every batch, I try.

To invest in around 20% of the batch.

Oh, cool. More or less. That's great. And I have been doing this for two years. Have you seen anyone doing cool hardware, cool consumer devices? I know that there's a ton of AI, there's some hard tail tech, defense tech's becoming cool. But I always like. I like the eight sleep because it's a gadget. You can give it for someone for, you know, Christmas, and they, like, experience it every day in a very different way than just nap on their phone. Have you seen anything? So.

I'll answer your question.

But it's cool because I walk around with my head and people stop me and they say, oh, I sleep on your product. I just met two founders and one I had a 75 score, the other one 48. Oh, no, that's 48.

The night we were down.

I've been smoking Jordy this week I got, I beat him twice. I'm up in the 90s, I'm doing great.

I've had a rough one.

But there is not a lot of consumer hardware. It's hard. It's so hard. Yeah, it's really hard. I was just talking to a few founders. Even when I look back, other companies starting with us, they all struggle. So we have been so lucky to be here today. But you see a lot of really cool stuff now in robotics. Yep, yep. Matic robots.

We really sit at home.

And so usually there is an arduin section and that is the first section where I go.

So hard tech or hardware, that is my passion.

Yeah, yeah, yeah. And then, yeah, AI is everywhere. Yeah, yeah. I mean, you see a lot at CES. You'll see the AI connected oven and the AI connected toaster. And YC's kind of stayed away from that because it feels like it's hard to build like an independent business around. But, but I am optimistic that, that once the software side of AI is so commoditized and so, so just ubiquitous, we'll see another revolution in hardware. Another. And I think with the robots, things will get easier because robots will explode and a lot of consumer will buy different shapes. This is what Nat Frieden was talking about. He wants the, the, the robot that picks up the leaves one by one instead of leaflet. And it's like a funny idea, but it feels like, yeah, it's only a couple years away and it'll just be a couple.

Even for security.

I have this idea about robot that goes around your house with cameras and lights. Yeah, right. I would immediately buy that it could go around my house and make sure that.

Especially if you could put a gun on it.

I mean, Amazon, Amazon did launch a drone that will. Or maybe they just launched a video about this. There's a drone that takes off from a base station where it charges and it can fly around your house and kind of. And kind of patrol inside your house. But yeah, I wanted that external.

When the fires were happening, I, I figured out that a lot of fires in LA are just started from a single ember landing in like a backyard or on a house or get stuck. And you just realize that, you know, there's probably an opportunity for drone based.

Yeah, there's actually a Couple companies that did like water turrets that you mount to your. To your roof. And then if they see fire, they can just spray right there. It's a hose. It's literally a hose on an articulated arm. It's like, not that complicated, but you could.

What about an 8? Any. Any other hardware coming down the line that you can talk, you can kind of allude to yet? So actually we have an office in sf.

So I just landed. I came here. I'll be here for a couple of.

Hours, then I go to the office.

To see the new products. Very cool. I'm already sleeping on the next generation.

That's such an edge. That's such an edge. You're on Pod five. On Pod, I'm already on Pod six.

All my friends, they always now make jokes because I always, always sleep on the next generation and there are new devices and so they buy the latest, but I'm already one generation.

That's your edge. This is how you win. We started working with some new sensors.

That are incredible in terms of computer vision. So we really want to double down on body scanning and scan your body while you're asleep to save your life. And that, to me, is one of the most exciting things, because if we can convert your bed in a health.

Platform and save your life, that's.

That's pretty sick. Yeah.

Yeah.

That's amazing.

What. What are the companies that you're most excited about in the batch? Without picking too many favorites out of the 20? Any. Anything that you're most kind of excited about.

At the end of the day, I just get excited with founders. I mean, I just met this guy and he's a high school dropout. He's 18 and he's. Yeah. What?

Yeah.

Yeah. Because I was at school, I decided to drop out. I thought. I thought there was this opportunity for.

AI to help teachers, and so I dropped out.

I built it, and now I'm selling it to my teachers.

I said, what?

That's amazing. I said, when you see these people.

Right. I don't even. I don't care what happens with your.

Company, but I admire you so much.

Can I.

Can.

Can I?

Of course. I want to back up the founder. Right? Exactly. And so that is what excites me, like to stay young and see these.

Generations shaping the future.

That's fantastic.

Amazing.

Well, thank you so much for stopping by. We will see you soon.

Great job, guys.

Thank you. Yeah, yeah, it's been great. Let's bring in the next team. Welcome to the YC Demo Day 2025.

Stream I put so much of the. The.

Yeah, yeah. It's okay. I'm working through it. How you guys doing? Oh, you guys already got the hats on. We'll see if there's. If there's other surprises in store, we might need to blow the whistle. Welcome. How you doing?

I like how you guys just said made in sf. Not made. Made with love. Made with.

Shots.

We have a made in with love in San Francisco as well.

Oh, you do? Okay, well, what is throxy? Break it down for us.

Explain the business we building AI agents that help people selling into traditional industries such as manufacturing. Distribution.

Okay.

There are sectors in which selling is very hard, especially from a B2B perspective.

Sure.

So we're helping those companies prospect into legacy industries.

Okay.

And we manage the entire outreach to those.

Okay.

Whenever someone's interested in speaking with my clients, I connect them with their buyers.

Sure.

And to help them grow. So that's like selling super technical products. What is that? What does that look like? Yeah, it's selling super technical products, but also professional services such as consulting. The important thing is we help people selling into traditional spaces, like manufacturing.

Okay. So. So, so there's a manufacturing company out there. They're making microphones, for example. I am a company that's going to sell, you know, better software design software that runs on this or automates the facility. You're going to help me find clients to sell to. Is this more about the prospecting and developing a lead list, doing the actual outreach? Is this an AI business development representative SDR play? Are we going to see a billboard on the 101 for you pretty soon? What's going on?

So it's a bit of like everything you've mentioned. So like, we don't like to Micro ourselves as AI SDRs because they have.

Like a bad reputation and we think.

Like focus is a multiplier on like the work we do.

And that's why we're like serving these.

Traditional industries, which are like traditionally like underserved.

Yep. Everyone's ignoring them. They're like huge market opportunity and like.

Really high average contract values.

So we can like have people serving.

These industries both with AI, but with a bit of human in the loop right now. And now we're automating those humans in.

The loop as models get better, as agents improve and like rolling them out. So talk about the copilot era. Where is it important for in the sales process to keep the human in the loop right now? What is the most automatable part of that process?

So the most Automatable part is qualifying the whole companies.

So like, okay, actually like we just.

Like pull a list of companies from.

Like our crawlers and then we look for like specific stuff with agents and.

We just qualify them.

Could they even be a buyer? Do they have budget? Are they big enough? Are they declining in sales? Are they about to get rolled up into some private equity things? The thing is like, because we're focusing.

Only in manufacturing companies, we can check.

For very specific stuff for like, okay, does this machine like fit like any specific specifications? Do they have like this grind type? Do they do like. Sure. CNC milling?

Yeah, that kind of stuff. Which is really important where like horizontally SDR fail.

Sure.

And they fail to serve them because they're too generic.

Because if I'm selling CNC software and some manufacturer doesn't use cnc, why should I even talk to them? So you're saving me time that way.

How did you guys get into this? So I think I was in sales. I was doing a lot of manual work myself. I've been an sdr. Three companies, completely different value propositions. But I think one of the big issues was actually finding the company I can sell to. I was doing all of that very manual research. Do they have buying power?

Do they have this specific certification?

When I was selling into hospitals, I had to check what their team stuff looked like to see where they fit my software. And I hated my life. I was like, you were still performing, right? You were putting up big numbers. Yeah, I actually was. And, but yeah, I generally felt like my, my job was going to be replaced soon. So I was like, let me, I gotta get ahead of this.

Let me replace myself.

Disrupt yourself.

Talk to me about what it takes to actually qualify a lead. What are the data sources? I've heard LinkedIn is extremely rich, but it's very locked down and they don't let you play with the API anymore. Obviously you can crawl around on Google search and some companies have a lot of information on their websites. Some of these manufacturers barely even have websites at all. How are you getting data?

That's our insight.

Like our Insight is like LinkedIn doesn't.

Like serve these manufacturing people because the owner of like a manufacturing company is not on LinkedIn, their prospects are not there.

So we've built our own like crawlers which are like crawling the whole Google knowledge graph from scratch and then like.

Sending agents to qualify these people which.

Have access to like specific tools with.

Directories of other manufacturing companies or API, like access to like machine specification, access to vision.

So we can like check out the.

Content of the website, like take a screenshot.

Oh, interesting. Take a screenshot. Hey, that's a cnc.

Exactly.

This is a CNC company.

Talk about traction. When did you guys come into YC with this idea and you've just been working on it or did you iterate towards it? Yeah, we came in with this idea in six months we've gone to 1.5 million in.

That might be the biggest one we've heard yet. Let's go. 1.5 million, baby. Let's go. Congratulations.

That's sick.

That's amazing. So the round's already closed, I imagine. Absolute dogs. Absolute dogs. That's fantastic.

What's your guys backstory? How did you get to yc?

We met in high school and we've always been like building stuff since we were kids. Awesome.

Pablo was like, I hate sales, but.

Like I love money.

I was like, let's go, let's go.

Build a company together. I was working in AI JP Morgan.

I was like the most boring thing to do ever working in a money.

So it's like, let's go do it for the money. That's amazing.

That's amazing.

How big is the team? I mean, it sounds like you've, you've already scaled this business a little bit.

Yes. So we're a team of four right now.

Okay.

Focus is very important.

Yeah.

So when you're asking where does humans perform better than AI, that's what we're testing is whenever AI does better, we're automated. But not. We have us actually doing that work.

Yep.

We want to be very thick into the workflow, understand the problem and at the end of the day, it's my reputation down the line. It's not the AIST of Throxy, it's me. So we're showing face in front of our clients and ensuring that this works.

Yeah, that makes a ton of sense.

Well, good luck to you amazing guys.

Congratulations.

Awesome. Thanks for popping on. Cheers.

We will talk to you soon. And we will continue our coverage of YC Demo Day 2025. We will bring in the next guest. I see some people out there. Come on down to the palace of party rounds. Tell us about your company. How you doing? Morfix in the studio. I see one hat.

Let's go.

Got to give out a second hat. How you doing? Welcome to the stream.

Good catch.

Come on down. Good catch. Who are you? What do you do?

We are morphic and we build open source multimodal search for AI agents and applications.

Okay. Open source multimodal search. What are. Give me some examples of the multi modality. What are we searching? Because some of these data sets I'm imagining. If you're trying to search over YouTube videos, YouTube is going to shut you down. If I'm trying to search across that.

No, that's a great question. So for multimodality, it includes not only like just plain textual documents, but documents that might have pictures, photos, images embedded inside of them.

Yeah.

What a lot of other people approach it as is trying to do OCR parsing on top. But that doesn't work because documents are.

Yeah. PDFs are a nightmare. The PDF spec is a disaster. We know this, We've known this for decades. It's not getting any better. Adobe clean it up.

What we do is we take pictures, pages directly as images and retrieve over those. That is much higher accuracy, much better performance.

Yep, very cool.

Are you guys going to be able to fix the photos app? Searching photos very hard gives us a chance. Yeah, yeah, Give them a shot.

Give a shot. It does seem like they're trying to do that type of multimodal search on cross of it, but they're just not there yet. In terms of like I'll be searching for, you know, a dog jumping on a couch. I know that I have it in my camera roll, but it's a video and that scene happened later and they haven't indexed it properly. So lots of opportunities. Talk about where people are implementing this. Is it enterprise, private data sets, Is it public? Scrape the web? I want to search everything, narrow it down. For me, it's a little bit of both.

The most adoption is in the legal tech space.

Oh, interesting.

Also in the health tech space, they have like lots of documents with like tables, charts, pattern drafting, for example, has like a lot of technical diagrams and.

Yeah, of course.

And it works really well for those people as well.

Okay, talk to me about the other major players in the space. We saw Glean Yesterday raised what, 150 million? At 7.2 billion, this feels somewhat adjacent. You're kind of eating off their plate a little bit. Is that a direct competitor or is there something different where you can play nicely with them?

Yeah, so I mean the kind of benefit for us is that we provide APIs and we're much more of a developer tool.

Sure, yeah.

And the way we see this going is actually not as a competitor to Glean, but like more of like a provider to glean. Okay, right. And not just Glean, but to people that are building like cursor for X and you need to deal with multimodal documents. Sure, that's exactly what we can help you with. So we're starting with search, but that's not it. Right. One of the things that cursor. The reason why tools like cursor and coding agents have become really good is because code is low entropy, which means you can predict well into the future what code is going to look like. One thing that we can do is help you get that low entropy with multimodal information. And so what video editing looks like kind of like three or four steps in the future. If I've got a clip and cut another clip, I kind of know that I'm going to delete the thing in the middle. Right. And so if you can use that and essentially provide that to models as like code, that ends up performing a lot better. And you can start building cursor for video editing and you can start building cursor for. How did you guys meet? What were you doing before YC? We're both brothers.

Oh, no way.

Yeah, before YC, I was a software engineer at MongoDB.

Oh, cool. And this guy, the open source thing. Tracks.

Dropped out of warehouse, Right? Exactly. Cornell. Nice.

Very cool. Yeah. Talk to us about the open source strategy. How closely are you mimicking MongoDB? We heard earlier on the show that MongoDB didn't have a managed service, a SaaS product, until they almost went IPO. Are you planning to monetize the open source program earlier? What is the play between am I using the open source version or am I paying? You look like.

Yeah, good question. The way we see it is for people who. If it benefits a single community member, then we want to open source it. If it benefits a team team, then we want to leave it closed source.

Interesting.

So things like SSO, things like connectors like Google Drive, etc. Or maybe like speeding it up for sure, like making queries much faster.

This is all going to fall apart when people start building one person billion dollar companies because you're going to be like, it all has to be open source because you only have one person.

Got to be a good problem.

That's a good problem. But, but, but digging in more into the open source, what's the traction been like? Do you have a GitHub project that has a lot of stars? What are you tracking in terms of rollout?

2,600 stars today.

Congratulations. That's fantastic.

4,000 monthly downloads.

Amazing.

Thank you, Jordan. 200 active deployments in production.

Fantastic. There we go.

Audience is probably mad at me. In the chat for that one, but it's amazing.

Yeah, yeah, it's fantastic.

You guys came into YC with this specific idea or did you iterate to it throughout? We came in with a much broader idea. We weren't too focused or indexed on multimodal before. We were like, hey, just, we want to be the data layer. What sort of helped us was trying to narrow down on the multimodal aspect, seeing how people are building more and just building on from there. Did you always want to start a company together? Yes, that's been a dream since we were kids, but yeah. Incredible, incredible. How's fundraising going? Fundraising is going well. We're kind of close, but yeah, looking. Looking to do it fast.

Another one. Well, congratulations. It's been great chatting with you. Good luck on the. The next stage of your journey.

Very excited.

We'll be. We'll be following along. Along.

Yeah, we're excited to use Cursor for video whenever. Whenever. That builds us. Send them our way.

Yeah, they'll probably build it on top of your company. So. Thank you so much for stopping by.

Thank you so much. Thanks for coming on.

Bye. Do we have anyone else? There's a little bit of lunch break going on. Giving you some inside baseball here at y Demo Day 2025, but we have one more team. They don't need to take lunch breaks.

They're owning purple.

They're working purple. They're owning purple. And the pit vipers have made a return. I think it's all one pair of pit vipers in case recycling.

We know the pit viper founder.

There's not enough color going on here. Let's put on some yellow hats. There we go. Let's just really get crazy with the fever dream that's going on with the orange, the purple, the yellow.

We love Clyde. Clyde, Clyde. What are you guys up to?

What are you guys building?

We're building automatic technical documentation for code base, so saving 30% of the employee time.

Okay, yeah, explain the first customer. Are you going after larger enterprises? Are you selling to other YC companies?

Yeah, ideally two enterprises, but we're starting off with series A, B onwards companies majorly, because that's when you start onboarding people. You need internal documentation to actually give like technical specification for your product, so on. So yeah, initial focus is series AP.

Specifically for companies that are delivering APIs that they sell access to you.

Not just APIs, but any. Any sort of. Like right now it's a web application, but any sort of application in theory. So like API is part of it.

Yeah, yeah. There's a number of open source projects that kind of allow you to stand up a boilerplate for open source documentation or API documentation. How is your product different? What, what are you hydrating? Because at a certain point, if there's kind of internal sacred knowledge around how an endpoint works, you have to get that from the person that designed it. Or can you instantiate everything from the code?

Yeah, that's the plan. Like the idea is for us to not depend on one person.

Yeah.

The idea is like we actually go across the organization, all the code bases and understand those like technical specifications like in the background.

Yeah, right.

So there's no difference.

How are you dealing with security? I imagine that if you're going across all the code bases, all of a sudden there's like secrets that could leak. There's. There's internal tooling that they maybe they don't want to have out there in their documentation. How do you think about that?

So we make it completely subhostle. So especially for an enterprise, they have to be compliant, of course, regulations and so on.

Yep.

So we completely make it self hostable. People can actually just use our product like it's packaged so you can spin it up with the repositories and. And nothing leaves their network. How did you guys get to yc? Like in terms of the place. Yeah. What's the backstory?

You want to go car? Plane? Yeah. That means, I mean through plane. That was the last time I've known this guy. We've been through so many places. I've known him for about 10 years. We met in uni hackathons. Tons of projects. Very cool. And to get to, I see just a couple of failed applications and here we are now. So many. Everyone has one at least. How's the traction been? What are you sharing today?

Yeah, so in the. We launched about two and a half weeks ago. We already are around 3,000 in revenue.

Congratulations.

There we go. We have about six, six, six, seven customers now. So we are. Yeah, it's going well. We have, we're increasing 30 over 30 week on week actually.

There we go.

Just do that for the next like a thousand weeks. We're good to go. Hopefully. Yeah. Never need to raise again. Nice house. Has fundraising going. You guys in the midst of it? Yeah, we are about 40 there. 40, 50 there. So we're getting, we're getting close. Hopefully.

Yeah. What is just you on the team right now? Do you have anyone else? Okay.

Keep it that way for a while or you think you'll. You'll start really? I mean, we, we are thinking of getting people on board, but yeah, we want to make it, we want to keep it lean. We're trying to automate documentation, so yeah, you got to live it.

That's great. Well, thank you so much for coming on the stream.

Congratulations, guys.

We'll talk to you soon. Bye. And we are ready for our next guest coming into the palace of party rounds. Welcome to the stream. The hum of YC demo day has died down as people move across the street to lunch. Good to meet you. How you doing? Nice to meet you. I'm Jon. Pleasure. Nice to meet you. How you doing?

What's happening? What's happening? Big day. Keeping up? Yeah, it's a big day for us.

Yeah.

How'd the pitch go? Smooth. We're gonna be in the. In the afternoon.

Okay.

How are the nerves? How are the nerves? Honestly, we are using.

Yeah, alumni. They do a good job of kind of like getting you so many reps that it just feels like anything else.

Honestly.

They work you up very easily. Introduce the company. What are you guys building?

So I'm Francesco, the founder of kua. Alessandro is the CEO. So we are building computer use AI agents.

Okay.

Meaning AI agents that can solve any problems like a human would do in the terms of clicking, typing, scrolling.

Okay. What at what layer of the AI stack are you working at? Are you sitting on top of just like a chromium instance or are you actually sitting on top of something like a browser base or do you can keep people?

Yeah, we wrap an entire operating system on a isolated environment, kind of like a docker for user agents. And that means that we can use system level events for injecting these commands like click, type and really any bash or powershell.

Yeah. And then, and then what's working in computer reuse right now? There's a theory that you just read the HTML at some point. Now there's more multimodal image generation. Like actually take a screenshot process that understand where to click, what's working.

Yeah, so screenshot is working way better than accessibility tree. For operating system in general, you don't have any HTML DOM to parse. Really.

You don't parse any of that system. You throw it all out.

We just like use screenshot, screenshot and pixel based model for that. And it also been proven by research that's working way better than interacting. What categories of agents are you guys seeing the most, you know, having the most excitement around traction? I think anytime you're building agentic infrastructure, you got to have Companies that are building great products on top of you that can be a challenge. But I'm sure there's a lot of other companies, companies in the batch. Yeah, yeah. So we haven't chased any verticals meaning.

That you haven't chased any verticals.

Any verticals meaning that we are able.

To figure out what people want.

Yeah, exactly. Because like actually we first month in YC we were getting the most esoteric ask from the users in terms of hey, I have this bunch of contractors that are simply three meme videos on video editing software on macOS. Can I use CUA for that?

Sure.

And like really we couldn't converge to like very common workflows and that's why companies that are our customers are chasing those verticals for us.

Okay, do you see the market fragmenting? Do you think you will find a vertical and niche down or do you want it all? Honestly, we want it all. Okay.

And we are here to.

Then, then what is the, what are the, the key deliverables that you have to optimize against? Is it speed, reliability, price, some sort of combination? How are you thinking about that?

Like probably for computer use AI agents, we are still like six months away from the ChatGPT moment. Maybe for browser use AI agent. That's still the moment is today. So once we get that level of intelligence for models we need to come prepared with a very good infrastructure to scale this isolated environment. Because our leap of faith is that five years from now most of the AI agent, a multi agent system, we rely on API. Maybe 80% of the scenarios and the other 20% are going to be based on browser and computer tools. What were you guys doing before this? I was working at Microsoft for over five years.

Oh cool.

Awesome. Myself I was a notion and I built also a few startups in the, in the past. Nice. Are you guys Italian? We are Italian. When did you come to the US three months ago now. Three months ago. 4YC? Yeah. Crazy. Crazy. Yeah. Has it been living up to expectations? Yeah, definitely. People ask me Ferrari or Lamborghini. Yeah. People ask me how is San Francisco now? Is it better? And I don't have any comparison. How old were you when you just when you knew you wanted to do yc was it? I think it was pretty recently. Like 3 years ago now. Okay. Yeah, for me maybe since I was 16 and I'm 26 now. So it's been like a long dream for me. Seen still like see I don't know if it's valid or not but living the dream, living the Dream. Yeah.

What's the go to market been like?

So the go to market right now we've been focusing mostly on startup and scale up because we wanted to prove that we were on the right path and eventually fail also faster.

Yeah.

But we have an open Source framework over 8K stars. Whoa, 8K stars.

Oh you hit that. You buried the lens.

Please go and start audio.

Yeah, yeah, yeah. Head over to GitHub right now. Give it another star.

Yeah. Try Kua.

That's amazing. Yeah. So yeah, I mean what's the monetization strategy around that open source project?

Yes. So we like first month in YC we were all this customer inbound that were basically asking us how do I even productionize on a computer agent today? So we are providing a pathway for the user from the open source to bring the same workflow that are working locally for them and scale them on cloud. So we're really charging only based on compute today you simply have to input an API key on our platform. But what's going to happen also for us, are we going to become a lam inference provider for these computer use AI models? Because maybe the public sense is that there are only two computer use AI models. Maybe the one from OpenAI and Anthropic and that's only because they have a better PR office than other models. But honestly like even on again face you'll find model from Bytedance UI Dask 1.5 that's also out beating OpenAI and.

Anthropic on computer reuse benchmarks on computer.

Benchmarks like OS Word.

Sure.

And they are so hard to set up and also hard to discover. And also we're going to be the go to catalog and platform where.

Yeah. How good are the evals right now are the benchmarks for computer use? It feels more abstract than just do some math problems.

Yeah. So I was actually working with the Windows team when I was at Microsoft doing about for computer agents on a benchmark called Windows Agent arena which is derived from OS word. Really like this benchmark tasks are not very meaningful. Like for instance you will find tasks like hey can you go and open VLC and add subtitles? Who's using VLC anyway? So that's the question. Even like using LibreOffice instead instead of like Office or even Google Docs. So what's going to happen? My leap of faith here is that the next generational benchmark will measure like real world task.

Yeah. Do you think there'll be a sort of like LM arena style benchmark where a human is watching Two computer use models use computers and there's kind of like a vibe check almost.

Yeah. Or even like a wiki race where you have like a wiki race. Yeah, even like you have now.

Okay, so wiki races, the idea is, is like, you know, you start with Y Combinator and you have to end at Christopher Columbus and how many clicks do you have to click to get from one to the other? So you might say, why YC has San Francisco? San Francisco is America. America's Columbus.

Yeah.

And so you, you try and race through and yeah, it's an intelligence test, but it's also, yeah, great computer use. That's hilarious. Yeah. But also, I mean, I imagine that there could be like a, like a big model smell like a vibe check on the computer use. Because if it looks very jerky and it looks confused, like that's something that might not even come across in a quantitative benchmark, but a qualitative human might evaluate it differently. Yeah, interesting.

Yeah. And also there is this whole problem, okay, I have this workflow that now is working maybe 80% of the time. How do I make sure that I'm able to reproduce the same kind of workflow all over again? So we're also working on episodic memory that will let you basically use RPA 1.0, the old fashioned RPA and UI automation for workflows that are very deterministic. And then say that you have a deviation from, from one trajectory due to noise or changing on a web page. Then that's when you use like full computer use when it really makes sense.

That makes a ton of sense.

Any other Italian YC founders? We haven't met many. Are you guys hometown heroes back in the Italian taxi?

You gotta go do the local press.

Yeah, do the press. Now that you're in yc, Delian does this.

Delian does this. Bulgarian. Bulgarian. He's a celebrity over there.

There is a wise key WhatsApp group now.

Okay.

They're aging like this week on the mountains.

Oh, yeah. That's reason enough alone to apply to Y combination.

Yeah. But then most elite group chat.

Yeah, yeah, yeah. Anyway, thank you so much.

Congratulations.

Thanks so much. Let's bring on the next. Do we have. Who do we have next? Oh, Delian, we were just talking about you. What's up? How you doing? Oh, you got the hat on already. Oh, my gosh.

Let's go, baby.

I can't believe you hit him with that. We've been doing that when we're here like big numbers, big ars. We didn't Bring the gong.

Should I? So I was a Y Combinator Summer 14 company.

Yeah, that's right.

Do you want me to go through my stuff? Summer 14, please. Give us the pitch. Give us the pitch. So, hi, everyone. My name is Delian Asparohov. I'm the CEO of Nightingale.

Okay.

We build software that helps autism therapists that work with young children to basically help them capture data on those children's behaviors. Put that into reports that you then send off to your insurance companies to get reimbursed. Today, all this is done by paper and pencil. Super manual takes these therapists like 30% of their workday just doing a bunch of bureaucratic actions. We cut that down, make it super fast, they get reimbursed more quickly, and they get to spend more time with the kiddos rather than on a bunch of paperwork. Cursur for autism.

I was about to say cursor.

It's cursor for autism. So if you ever wonder where all the autism came from, it's because my first company, literally all I did was spend time with autistic kids. And so, you know, if I had some in me already, it got amplified.

How did your demo day go? Did you raise, like, what was it hard to raise back then? It feels like everyone here can put together a million dollar C grant.

What was like the. The comp that you use a lot of. A lot of YC companies obviously like to give some anderol for dog walking. Yeah. In like summer 14, like, you have to remember, like, at the time, it's not like there was a ton of like healthcare SaaS, things that had worked. It's like you had like, Epic is like an EMR that obviously done super.

Well, but it was epic. The story fully. Yeah.

And like, we weren't really an emr. So honestly, I think like, you know, I remember like Sam at the time because he was like the head of YC back then. You know, two weeks before demo day, basically told me, like, your pitch is fucking trash. And then I went and. And you know, we're gonna say this on live stream, but yeah, I took some psychedelics on a weekend and like, you know, really thought about my pitch, you know, for that weekend, made a lot of improvements. And then Sam afterwards told me he was like, you know, relative to where your company's at and like, performance, phenomenal presentation, but phenomenal presentation in 2014 turned into like 600k seed round. That was a grind. Two months after demo day, like, you know, doing individual calls. Crazy. And it's just like when you look at like the amount of capital that's like, you know, whatever, like the next next door building. There was, there was, there was like a two. Somebody said there was like a two hour wait this morning if you tried to show up like right at the start there was like the line was like two blocks down. December 14th, like we like filled up like a small little like area, like cocktail area in like the computer history museum down in there. So it's like I. I just. If you just given 10 grand to like every batch member with you, you would have a billion dollars now. Yeah, I think summer 14 did have some hits. I'd have to go back and remember summer 2012.

My batch had a ton Coinbase Instacart. That was a gap year. Yeah, it was a good batch of good ones.

But yeah, it's interesting to study. Just like, I feel like you can use demo day. This is my first time coming to demo day in like I think seven years or something like that. Partially like in 2018 I went, spent a bunch of time on it and like, honestly just like didn't lead to any investments. And so I was like, at some point, what am I, you know, doing here? Then obviously Covid really killed it off and so excited to be back. But it's also an interesting just like marker of like the like the industries, you know, sort of maturity of just like like the amount of companies, what the companies are working on now. Also the amount of comps that like you can like look at. Like in 2014, if you had said like my comp is like, I would like to be a hundred billion dollar publicly traded company. It's like, okay, there's like basically like two of those in the entire history of technology. Now you have to come because people are doing Varda for X. Gotta track those guys down and figure out how to like acquire them. So we have like a desi Varda. Yeah. Have you, have you seen any of the hard tech companies yet? Any of the pitches? Gary said like 11% of the batch is hard tech. Yeah, yeah. It's interesting to see like, I mean I remember in like 2018, 19 when I was doing like hard tech industrials, defense, aerospace, it was just like so uninteresting to so many people. Like they would all like literally like, you know, we talk about this like ever at my former colleague, he's just like, oh, like if anything is like, you know, negative gross margins and like highly capex intensive Senate, he like said that as a joke.

Yeah.

And then everybody's Realizing like actually Capex intensivity is like the best mode ever because like if you just build software, AI slop can, you know, replicate it basically overnight. So yeah, I definitely looked at it, you know, handful of them. I think it's cool to see that like YC is leaning into this because it's not something that they've had a.

Couple hard runs with. Like pebble was a bit, was a really big like hard go because like they got so Sherlocked by Apple with the Apple watch.

Totally.

Yeah. What are you going to do? But at the same time like there's been now like Astranis and Oklo and like a few really even harder tech companies that have made it through and like scaled so astronauts I do think.

Is like the best like OKLO obviously like you know, sort of, you know, sort of you're trading but like you know, hard to figure out.

Yeah, hard to figure out but still.

But Astronis feels like it's like it's got some, you know, sort of works another one 300ft down. Yeah, I admit though, like look, I think like, I mean if you look at you know, the like YC Deep Tech, you know, sort of portfolio and like hit rate and outcomes relative to like the FF or Delian Seed Deep Tech Industrial portfolio, there's definitely one that I would want to buy in the basket of and one that I wouldn't. And so you know, I, I mean maybe I shouldn't be speaking. Maybe Gary's gonna fucking kick me out.

I think like the bull case is that like, like it is great to have exactly what YC is, which is an incubator and accelerator, like a pool for that type of talent to come out of and if you wind up picking over at it at some point, like that's fine and that actually part of the ecosystem. And yes, like you're gonna get earlier stuff but it's nice that there's at least an ecosystem. Some of the people that go through YC with hard tech, they might become employees at these companies, they might become acquisition or acquire.

It opens the overton window for like the average and like not just how many multi stage VCs have pulled back from, from doing demo day investing at all. And just saying, you know, we're not going to try to go. I mean I feel like in like you know, sort of 2019 it was like the consensus thing like at some point like everybody was like why are we doing this? It's just like way too many companies, they're like, you know, sort of seed Rounds, you know, feel like. And again, you know, maybe Gary's gonna kick me out for this, but it's like the seed rounds felt like they were really overpriced. And especially as a multi stage firm, it's like, well, you can just wait for the series A and like on a risk, it's not like the companies are gonna die if.

Oh yeah, so many yc specific funds that would come in and just write 100k check into tons of companies. So like everyone was getting their rounds done. But yeah, I mean, yeah, it just speaks to like how they're playing. Also there's this weird dynamic where YC used to say, like, I don't know if you got this advice, but it was like, don't pitch any investors until YC Demo day. And then everyone was like, oh well, like the game theory is like, if I'm the only one pitching before demo day, I get all the interest and so, and so like, there's still like, I'm sure like you will, you will take a pitch with a YC Demo day founder a couple of weeks earlier because they're inventive and creative and they.

Got to you before totally.

You just might not find them through this.

I do think there's some amount of like, a lot of the like, you know, companies have already closed their rounds by like the time this day happens, which is very much so not the case in 2014. 2014 is like, oh, maybe one company, entire batch.

Yeah.

And by the way, for what it's worth, like, if you study those like early batches, there was basically like an extreme negative correlation between like the ones that like, you know, sort of raised early and that actually ended up being like the like, you know, sort of batch returning, you know, sort of outcomes.

I remember there was one company in YC Summer 12 that had a super viral video because they were in the viral video making business and so they got a ton of attention and they'd also like, kind of ramped revenue by like saying like, yeah, well, we'll produce a video for $100,000. Like, that's not really like, like durable scalable revenue. That made the $60 million round before demo day. And everyone was like, Christ going on Coinbase. Did you see that?

Did you see that ad? It was a company called CO Tool. They did like a skit based on the deal rippling thing. No way. You got to see this video. But they're in this batch.

Yeah. They have a service that will monitor slacker chats for honeypots and create Honey pots for you and do all this different cybersecurity stuff. It's great.

I mean, I think back and like, I just had this memory from 2017 when I was at Coastal Ventures where like, you know, Vanode to basically have like the junior team go through and like crawl through the entire batch of like everybody, like the week beforehand, basically on the Sunday night before, like the like, you know, sort of Tuesday demo day, we would invite like 15 companies to present at KV on Sunday from like noon until like literally midnight. We would be there. Like I remember like letting founders in at 11:30 at night to like come pitch the firm. And it actually felt like we had this like really deep arb. It was alpha, nobody else is doing it, etc. And then literally it's like, like you said now there's like these infinite sort of YC funds where like, I actually just feel like the alpha there. I'm like doing the pre work, etc. Getting into it. It's not to say there might not be some good outcomes, but like many, many more people run that strategy. And then even the fact that like something like this exists, like the idea in 2014 that there'd be like a live show that anybody would give a fuck about and actually want to tune into, to talk to, broadcast, we could barely get anybody like, you know, pay attention to any of us, let alone the idea. There's like, whatever, gonna be like 15,000 people on Twitter. So yeah, this entire industry has just gotten like, you know, I mean like, this is. We are like the new Wall Street. It's like kids grow up, you know, in like 2008, being like, I want to be like an investment banker. I knew I wanted to join YC when I was 16. He's 26 now, so it's like decade. I mean, we talked about this in relation to the like, Thiel Fellowship recently. Recently where it's like in 2012, the like off track thing to do was to like drop out, build a company, join an accelerator, work in technology. Now this is the track. And so we like need to practically find high school drops. There's a high school dropout in this batch? Yeah, yeah. I mean, at this point, like the kids are.

There's an article in Business Insider today by Julia Hornstein, who wrote the article about the first article about us talking about how like not just not even going to college at all is the new drop out.

It's like just the default. It's just the default versus, like in my year, to my team member, there was like three of us. He has applied to college. Get accepted.

Yes.

And then don't brand name be like MIT acceptee. But that's all.

I had a whole riff on this. It's like, yeah, Delian, you dropped out of mit. I knew that I would drop out if I went there, so I didn't even apply. But it's just like, yeah, yeah, you're a sucker for even having gone for a day. I didn't even go to application.

You paid the application.

You made the application.

Paid a full year of tuition. God damn. Boomer back. I could have put that in Nvidia and I'd be a billionaire.

Boomer mode. Anyway, thank you so much for stopping by.

Good to see you boys. We got some big news. A new investment from you coming on. Oh, yeah.

Tomorrow, we'll see you back to back days. Welcome to the Demo Day Stream 2025. Good to meet you. How are you doing? I'm John. Nice to meet you. Dave.

Dave Munich. Did you photograph us out there or was that somebody else? No, I didn't photograph you. Who was photographing your buddies? Someone else at GV Han. Okay.

He took a picture.

Oh, yeah, we love the paparazzi.

It was good. Can you introduce yourself for the stream?

Yeah. So, Dave Munichello, Google Ventures managing partner there.

Fantastic.

Been there about 13 years. Investing in AI and enterprise software from the early days.

Lots of good stuff to do here.

I was just standing in a room downstairs hanging with a bunch of folks, and Gary came in and said, hey, you got to go do this. I mean, I mean, thanks for coming on. I'm here. Excited to hang.

Yeah. What, what, what trends are you following? What are you seeing that you like? What's interesting?

Well, first break. Break YC into Chapters for us. From your point of view, I'm sure you invested in companies at this point. Maybe not on right around demo day, but in every. I was in Cambridge in the early days in grad school when like Paul Graham and those folks were in Cambridge doing their thing. So at that point in time, YC was like the cool place to. To be connected to.

Totally.

And I think, you know, a lot of us. I met, you know, a partner of mine that now runs our life sciences team and I co lead our digital team here at gv. We met in Cambridge and we used to like, get really excited about any Cambridge YC events.

That's amazing.

So the place has totally evolved.

Oh, totally.

Right.

It's a machine.

Chapters Totally was fortunate enough to do GitLab in the early days, so like new Darwin from day one. And like, Sid has always shared his enthusiasm. Patrick Collison is a portfolio founder. Comes in and talks to the batch and then we hear the cool stuff from him.

What was the perception around GitLab at the time? I feel like I remember it and it was kind of like discounted because it was open source. GitHub was already such a success. It was like, how are they going to do anything when there's already this winner?

I literally just stepped out before this. Stepped out to do the earnings call with the CEO and the CFO to do the investor callback because we're public market shareholders of the company. Oh, wow. So we invested just after the Series B. Yeah, we actually passed on the Series B. Oh no. Weird. And we had a bunch of concerns. And if I look at those concerns, they were. Hold the mic a little bit closer. Just angle it. They were one of the first companies to be remote only.

Oh yeah.

That was WordPress and GitLab.

Yeah.

We're like this remote only thing seems strange. How are they going to run a company like this?

Yeah, yeah, yeah.

Sid is extremely technical and I think remote only works really well for him because of the way that he shows up as a human. But he writes everything down and so that works for a subset of people in society.

So we wrote down GV passed. And he still let you in.

I mean, we talked constantly, like passing out a company, it's just like this stage isn't right for us. But we want to continue to talk to you over time.

Right.

What's your approach to demo day now? I'm assuming you don't have a lot of FOMO. You guys write bigger checks. We've met something like 30 companies so far. You are writing checks even at this early stage? We write checks into YC companies. We love YC companies. So even though we're multi stage, like $100 million into a public company, as we were just talking about, we also do seed and everything in between. A is our sweet spot. A's and B's great. We do like an event a few weeks before demo day every year with all the YC founders and then we know all the group partners. Right. So they like constantly ping us with ideas and stuff.

That's great. What is the integration with Google like now?

We're entirely separate.

Entirely separate.

Yeah. So we raise capital from Google. It's an LP relationship.

Yeah. Because it's such an interesting dynamic. Because on the one, on the one hand, like that could be incredible value add. It is like, hey, we'll introduce you. You can sell into Google.

The incredible thing is we have a stable LP that's there forever. Permanent capital, essentially, plenty of capital and an appetite for risk. So we have a great LP that we have a half an hour conversation with every couple years and. And plenty of capital. Well, we don't spend any time pontificating about where we think the market is. It's why I had to call our comms people before I came on here is like, we don't, we don't usually do, you know, marketing or like comms events or podcasts or stuff like this. Excited to talk to you guys, of course. But yeah, I think we're unique in that we spend all of our time with founders. Yeah, so I shared the, like, it's. I was such a hack. I mean, I think you're the envy of every. No matter how successful, our GP friends and the GPS on the show, having a dynamic where 100 people could call you on a Saturday at 5pm and you kind of owe them your time to some degree. And that's like that LP dynamic. I talked to, obviously, tons of friends at the GP level across different firms. It does keep them sharp. Like, they get a lot of pressure from LPs, constant questions, deal flow, connectivity. I think that's really positive. But we don't have to deal with a lot of that stuff. And so we spend time connecting with brokers and other GPs.

What do you think the nature of those questions usually are? Is it just like trying to understand markets and trends and how the questions from. Yeah, I haven't really sat on that. I've been to like one or two LP days.

So what's this transformer say?

I didn't want to say it, but I've seen kind of the wrong.

I've seen the movie, but I mentioned this idea of like, we invested in, you know, GitLab in the early days and then now they're a public company. Hedge funds invest in the stock.

Sure.

Call us to ask us for our perspective.

I'm sure.

And they're thinking about like, what happens in two weeks. And I imagine LPs are like, slightly farther out. Like, you know, what's, what's happening today, what's hot today, are you in the right deals, that sort of things. Our LP doesn't care about any of that stuff.

Right.

We don't have the conversation about, like, what, what we're in, what we're not in, etc. It's like, do you have generational founders?

Do you have a particular understanding of how the startup landscape is interfacing with the Mag 7, the big tech companies. Right now we're in an interesting time. The big tech companies, they all kind of like went from 100 billion in market cap to a trillion very easily. And it was kind of like, it was kind of like the easiest 10x of their entire career. You know, in kind of some sort of unexpected way. You would think that would be the hardest one, but a lot of them just did it at the same time. It feels like there's more opportunity for startups than ever, but the big, big companies have more resources than ever. What are you talking to founders?

I mean specifically around, I'm wondering constantly like is AI going to make incumbents stronger?

Does a magic sustaining innovation.

Totally.

And yet I'm talking to companies that are doing millions of dollars in a RR over two days.

That's right, that's right. And I think the question for us is, you know, does each incumbent, each big SaaS company, do they bolt on AI?

Sure.

Do they acqui hire?

I know, yeah, we're seeing this with the Windsor thing. Every big tech company.

Yeah, yeah. It's a new hot structure. Yeah, it's the new M and a. I'll take 49 and all your best people.

Yeah. I could do this valuation or double it and you get half. It's like the same number.

But I think having loads of capital right now in a time when like the seats are shifting in tech is quite interesting. The Mag 7 might be the Mag 70 in the next 10 years. Right. Add a zero to it.

I would like, I would like more tech companies. We're on the side of big tech and so we, we, we, we, we, we want there to be as much.

This is actually Little Tech. The 70 would be little. But we're, we're, we're fans of all of it.

All of it.

Just high tech fan tech. Yeah, yeah, totally. Yeah. I, I, I think this idea that like people want to make people want to say AI is good for big tech or it's an extending innovation but it can be good for both. Right. It can be so transformative. Like the Internet was good for some big companies that adapted well to it. It was good for a bunch of completely novel ideas and so we don't have to like pick one and pick a side. It can be an extending innovation and it can also enable all of this.

Yeah.

I think we're in this exciting place where like the most high agency humans in our lives that we're all connected to they're empowered not just to have like the underlying cloud be present for them but intelligence be present for them. And so now they're building. I met a company out there that was like one person. No engineers already have tons of revenue. Like I think that, you know, he told me he's going to be the first billion dollar company.

Oh he's going for it.

Right. I always get, I always get hung up on that because it's like if you attach, if you attach it does.

Feel like a vanity metric.

It's a van. It's a total. I mean it'll be amazing when it happens but a total vanity metric that can like guide you towards bad decision making.

But it feels like it might like happen accidentally if it happens happens actually something that's maybe delivered or the way.

To do it but it's good mark and then lay off every other person but yourself.

Yeah, yeah. The private equity guys are really going to be the ones that do it. They're going to be like, yeah, we bought Intentional Person company and we fired everyone except for one person.

There are a few VC companies right now looking at VC firms that are looking at, you know, the PE roll up.

Sure.

Like something that has massive distribution.

Have you looked at anything?

We have looked at them. We have passed on a lot of them. I think it's. It feels like a PE play where you're trying to like it's hard to change as a result of the industry doing.

It's all.

A lot of the founders that are running that strategy they just should change the structure and just say like we're going to run a PE playbook here and we're going to be doing 20. We're going to be 2 and 20. Yeah. Because it's. If you can, if you can raise 20 million on 100 for the strategy and keep like a lot of the economics. Sure it's great for the team but it should probably be like the. Basically the, the comp incentive structure should be look more like private equity. Totally for.

Yeah.

You guys are friends with a buddy of mine. Sean McGuire's been here a couple times.

Of course.

Sean introduced me to a founder on Friday night at like 9 o' clock over text and I respond back and the guy's like do you want to meet tonight?

Nice.

Do you want to meet tomorrow morning? Like I'll come to you. I live like an hour away. I'll drive to you. I'm like that, that kind of high agency human is going to be empowered by you know, an entire set of Tools, a whole software suite. You know, I will be the thing that powers all of these incredible humans that we're sort of of meeting today for sure. Yeah. The thing. I hope we get some more of these companies on. We've had a lot of developer tool teams on. I think this idea of like business automation is being heavily explored around agents. But we were talking with Dylan Patel last week and he says like the next category besides consumer tech, you know, with like LLMs, like you know, chat GPT, then you have, you know, code gen as like big revenue categories and like this third category of, of just actual like business automation. So like how do you just make the machine work? Yeah, and everybody's thinking about it in the concept of like agents which is like kind of, I think like almost a simplistic way to view these things. And like what is the next, what is the next iteration of that where it's like actually like an autonomous system that doesn't have to interact like a regular employee. It's sort of. So we'll see. Yeah, I mean we're seeing it across an organization like a Sierra or a Decagon, you know, in. And Harvey is a legal AI company that we're invested in. There's some medical AI company. So like every vertical has AI, but it looks a lot like a human. It's like a replacement of a human. It's replacement of a human. But how do you replace 20 humans at once across functionally?

Yeah.

Do you worry when a YC deal that you're looking at gets hot? Do you worry? Do you think it's a. We don't worry at all. No. But I mean historically, you know, if, I think if you do look at the data, a lot of these companies that some of the hotter companies at demo day don't end up, you know, always. I mean we're investing in super hot companies at the A and the B and the, the most sought after companies get marked up incredibly.

Right.

So it's a sign of the heat, is a sign of enthusiasm from great people, talent, opportunity. Yeah, totally. And so like you have to, if you're, if you're choosing to get exposed to that asset class, you have to be willing to pay the price of, is to enter that asset class and play in that asset class. Here the challenge is that you have like three months of data. Yeah. And so you're talking the company that grows revenue the fastest in two weeks, three months, whenever they actually launch is not necessarily the company that's going to grow revenue the fastest over two Years, three years. We've seen that a bunch of times where we invest in a YC company and then after demo day it kind of chills out a little bit and then it re. Accelerates.

Yeah, that's good.

There's a founder and batch. Yeah, total founder in this batch that raised I think like almost $8 million of uncapped convertible notes. Right. And so it's just like humans dog.

An absolute dog.

He's incredible founders, incredible team and like I understand why people are sort of leaning in to working with them, but that's pretty difficult. Yeah, yeah, you're thinking about that next, that next call in a year or two with Google being like, you know, trying to explain like you know, entering a party round on an uncapped note. It's easy to just literally has no visibility. Yeah, sure, that's good. So maybe it's easier for. But for us, the thing that we care about is we want to be your lifelong partner. Like the thing that we think about for founders is how can we be for them there for them over every round and into the future. What's your messaging around signal risk? Because I think there's this like, if you're truly a multi stage fund, you could do an early round and you could could say, you know, we're good with our ownership right now and like we're going to help you raise this round. But we actually like, I think this concept of like signaling risk is like totally possible for you to want to invest in a company today and three years from now. So like just because you don't do the in between rounds or. This is the exact conversation I was having when Gary walked up and said, hey, talk to these guys. So I was talking to Neeraj from General Catalyst.

Oh yeah.

And we were chatting about like, do you play when the price gets to an uncomfortable place? What signals that send like you're essentially sending a signal to the market that your firm is excited about this company. They have a separate seed program so they can kind of categorize this as like, this is a seed bet. We're going to put a million dollars into this company. We'll see how it goes. We don't have a separate seed program. When we do an early stage bet, we use similar criteria to what we use in the A. Obviously they don't yet have a metrics, but the question is like if they had a metrics, would we lead the A in this company? So there is a big signal when we do it. So it makes it harder for us to do like 30 or 40 companies. Yeah, we talked to 30 or 40. We might do a handful.

Yeah, makes sense. Very cool. Well, thank you so much.

Thank you. You're welcome. Take care.

Good to meet and we are ready for our next team or individual or investor or yapper. Who will it be? We will be surprised because we are YC Demo Day 2025 welcome to the stream. How are you doing? Good to see you already have the hat.

Hi.

Hi. How are you doing?

We're looking around for the camera.

You're on live. You're on a live stream. You'll need to introduce yourself. You can wear your hat. You don't need to wear that. Whatever. Yeah, don't wear that.

John. What's up? Andrew Jordy. How are you guys?

Introduce yourself.

Hi, my name is Andrew Lee. I'm a partner at Andreessen Horowitz.

Fantastic.

Both working in the games fund and also at a 16Z speedrun.

Very cool. Are there any games companies here today?

There are no games companies here. None. Which is somewhat sad.

All into SpeedRun.

There'S about four or five of them. I would say that for YC there's about four or five consumers companies which is pretty good.

So you can look at those for sure.

For sure. Four or five in the whole batch. I mean there's like five or six ish still. But here's the good thing. I mean like there were a couple companies who previously in the past were like B2B companies and they're like, you know what? This is really boring.

Yeah, I don't want to do this.

And a number of them like ended up in gaming and they ended up in entertainment. So that was exciting. And then also I just generally think that like if you're going to build something that's that, you know, your mom or Your, your, your 17 year old DGEN friend is going to go and play then. Yeah. You know, it makes sense for them to go and build B to B2B stuff as well.

Yeah. I want to talk about the games fund. I've been super interested in how hard it is to get into the hot games because they kind of blow up out of, out of nowhere.

You're like getting on a plane to Sweden. By the time you get there they've doubled. ARR.

Yeah, there was this Balatro game that was a massive thing there was among us. Was that the one? Yeah.

I mean that was probably one of the top ones ever played during COVID.

During COVID like these kind of like flash of the pan games that become very viral But I don't understand if they're like necessarily good businesses.

Yeah.

So like how are you thinking about finding great games or games related companies or even just consumer companies? Like what are you looking for? Because the signal seems so much more noisy than in. If there's noise around a, like an enterprise dev tool company, like they're probably selling that and it's probably going to be pretty sticky. Whereas like Balatro, I don't know, it seems like local funk. I think his name is fantastic developer. But who knows if that's like a. Going to turn into like Activision.

I think fundamentally for us, the way that we tend to think about it is there's, there's like a couple different things to care about. One is that if there's a large audience that has a bunch of folks that are going to play, if you do one innovation in that audience that makes sense, for example, big fans of League of Legends. If you're all out there, if you're trying to create like a moba, that sort of makes sense.

Sure.

But I think that for us, honestly the big wave we see is in the world of AI. Sure, right. Whether it's like changes in 3D animation, we fundamentally think that the future of entertainment is actually going to be. There's going to be an AI Pixar. Mark my words, someone's going to make an AI Pixar. It may not actually even be Pixar. Right. Because usually what happens is we tend to think that like an incumbent, for example, like you know, Disney or something like that, which exactly is going to make like the next thing or potentially take the next wave. But I don't know if you guys seen any of these videos.

Oh, incredible.

I mean, the Bible Bros, the whatever, like like Stormtroopers walking all over the place. I'm like, it's astounding. And it's. And I don't think that's something that could ever occur. There's like a sort of innovators dilemma that's occurring with the existing folks.

So even just from like a PR pressure, like, I don't know if you saw that, that show, the studio, there's this whole sequence where they're very worried about the casting for this new Kool Aid movie. And then it is revealed that no one cares about the casting. All they care is that they used AI a little bit. And it's this really hot button issue. There's massive PR backlash. And so that's this counter positioning where if you come to the market and you say like, yeah, we're we're an AI Pixar. We're just making AI stuff. You don't have the expectation. People expect Pixar not to use that.

That's right. How are you thinking about investing at the, at the game layer versus kind of the infrastructure layer? It feels like there's a bunch of new tooling around just creating these generative worlds turn into games. And is the, is the roadblocks of AI Roblox or is it something, you know, new? Yeah, it's interesting because I think the thing is what we've seen is well we go where the founders go and it seems the number one area that the founders are going is into more tooling and primarily using AI. I mean there was a bunch of stuff. There's still a ton of I think experiments happening in the web three layer, potentially in the content layer. But the main problem is honestly is that distribution is tough. I don't know if you guys are like invested in any consumer companies lately, but it's hard. It's hard because there's a reason why every DTC company has basically had all their margin eaten by, by all the big tech companies. Right. And fundamentally I think that's the same problem. And Steam which is like usually like the platform for folks who want to build games is not nearly as liquid as it possibly could be.

Sure.

So as a result I think the thing is the one thing that I think we've seen that's very positive out there. Liquid as in there's not enough demand coming from Steam itself or really that like your ability to get more bang for buck. Right. Like that it's fast enough that you don't have to pay a huge amount of marketing spend. Yeah, it's gotten a lot tougher and you have to be very good at it. So there's great teams that are able.

To gaming going on on there too with like wish listing driving sales and so you're paying people to wish list your product and it's like there's kind of schemes on top of schemes.

Right, right. And the thing is like I think we could, we could do it. I mean like there's only people who do that. But it just seems that if you create a 10x product that is able to grab some great cut consumers out there, that seems to be something that has natural growth. I mean I'm sure we're all familiar with midjourney that was built. It's built on Discord. Yeah, yeah, still in built in Discord. It's not as if it was something that naturally would have grown. So the thing is, I think the, and obviously I'm talking about Veo because that's like my latest thing that I'm just doom scrolling on every single night. But when you can basically grow from zero to all of a sudden 120,000 followers with four videos over the course of like two days, that's an astounding thing.

Right.

And if someone is able to do that, that shows me that there's like a natural consumer pole. And that's the thing that's pretty interesting. So mark my words, I still think that there will be an AI Pixar. I also think that fundamentally the world of AI, tech and entertainment are going to converge and we're going to basically see somebody create that 10x product that then hopefully just basically skips all the distribution problems.

Sure.

But I don't know, who am I to know? Are you, are you seeing, are you seeing enough here? Are you seeing enough weird stuff? Right? Like there's this concept of like, you know, kind of trying to leverage AI and the sort of existing paradigm. But when you think about the intersection of like tech and AI and entertainment and sort of like, you know, I can just imagine like entirely new ways of playing games. You already have kind of seen this on some of these, you know, people basically creating games within games. But yeah, but are people being, are people being like, is the average pitch really trying to rethink things from the ground up or is it, hey, we think we can build the next Candy Crush? Yeah, I think a lot. Well, for us as a fund, we'd want to obviously have people who are going to be willing to build the next unicorn company. But that doesn't mean that I think great developers out there won't create amazing experiences. I definitely agree with you that you have to basically aim for the weird. You have to do things that are basically in the frontier of what's possible. Because otherwise then what you're doing is you're most likely just like basically doing a me too, which is then hard because in a distribution channel where you have to basically pay for your customer acquisition, that's like super hard. I think something that that's also pretty interesting that I was telling some folks about was that the one thing that's interesting about both consumer experiences in games is that if there's a limitation, take for example on, let's say that like you can only network 20 people on a server together, Right. Well, the way you do that then is you just make it so Your game has 20 people playing all at the same time. And there's things thing called Fortnite and then 20 people have to kill each other all and then it eventually ends up with only 20 that you'll be able to go network with each other.

Sure.

So the good thing is you can just basically change. It's not like a bug, it's actually a feature. That's kind of interesting.

Yeah.

But I think also generally what we're seeing in AI though is when it's. You guys are probably familiar with this, which is the sort of cycle between B2B to the, to the app side, which is basically you have B2B infrastructure that allows you take for example, to create really powerful video models.

Yeah.

That then allows you to have apps that use those video models and then create content, that create new network models, for example. And then that leads into other things happening with the infra layer. Yeah, we're seeing a lot of that happen.

Unreal engine was a B2B play.

Exactly.

Birth Fortnite. And then there's another company in the Andreessen portfolio. Yeah. That does kind of like world scale sharding so that you can like basically build like a big MMO that you can walk through. I forget what this company is, but they were doing like some scientific computing and some economic analysis. That was years ago. But there's obviously a lot of work done on the infrastructure layer. And are they going to be the one to build the next great consumer game? Maybe, maybe not. Maybe it's built on top of their platform.

What are you seeing in VR? In VR? Let's see here. So we have. There is one great company that came through before from Speedrun in the past and around the first one was a company called Tras Games.

Okay.

So, you know, it's one of those things where basically I think just like people grew up in the mobile generation, you need to have people who grew up in the VR generation. So if you talk to anybody who's under the age of like 16, most of them will be like, I play a lot of VR. Really? It's crazy. Like they all go home, they just play VR a lot and they have to obviously have the device installed, but for them they spend a lot of time there. So we backed this team that was like a bunch of teenagers who like they won a bunch of Apple Awards and then they're just like, look, we just spent all our time in VR. So they built a game that basically is taking one of the bigger ones, attacking one of the bigger ones, which is Gorilla Tag. They made a Game that is is astounding. Their, their, their most recent game actually, it's called Yeeps. Yeeps actually has, you know, I, I can't describe it because I'm too old, but basically it's like, you know, we're all in a world together and we get to go and do stuff together, but then we all collect yeeps. We yeep at each other.

Okay.

And it's like we're yeeping. Yeah. All the shout outs, all the EEPs out there, but, but, but they're doing great. Because the thing is, I think ultimately it's not just a hangout spot for a lot of these kids, but it is ultimately taking advantage of, you know, what VR and the, the general install base. I think, I still think that like VR still needs like a shot to the arm in terms of, you know, we all know this, that it probably needs more installs. It probably needs find a, find a.

Way there, but it, it needs like higher, lower churn relative to the device sales.

That's right. That's right. Or the device sales have to be way less expensive.

Yeah.

Or find a way to, you know, just get as good of sales as the meta Ray Ban glasses potentially.

Right.

We need VR games that are truly addicting, not just novel.

Yeah, yeah. I was really hoping for the first.

You probably shouldn't.

I mean, I remember, I remember I like eeps though.

Like, and the kids love it too.

With, with the original like PlayStation, like Metal Gear Solid. That game was like 100 hours or like Final Fantasy 7. That was 100 hour experience. GTA 4. Yeah, that was like 100 hour experience. And I've played a lot of VR games, have yet to find one that it's like, okay, the progression in this game is so addicting that I need to keep putting it on to play. It's like, it's like more like, okay, it's cool demo. I said a high score. Okay, I'm done. I'm not like, I need to finish this. I need to know where the story goes. And, and it's hard because it's a very expensive investment.

I mean, I think that's why it's easier honestly, if you're going to innovate in the world of entertainment and innovate on that B2B layer, which is where we're seeing it. We're seeing a bunch of different, of AI sort of video creation tools. We had one company, Hydra, who came through, who was honestly just astounding when the studio Ghibli sort of Content started exploding. People were like well how can I animate the studio Ghibli content? And then everyone was using Hydra as.

Oh yeah, I saw that your partner did.

Can we have a studio? So the magic of Studio Ghibli was that it could one shot these beautiful outputs and has there been. Are you in interested anticipating that kind of moment for sort of ephemeral gaming where I could like take a picture of the three of us and say like make a boxing game where we can like fight and you get swords and then it's like it creates that and it's like fun and viral. Can that happen in the near like are you expecting that at all? Well, never say never. I, I think that ultimately we have to get past this sort of distribution problem. But my hope is that it gets a mid journey moment like, like we've had in the past. And the good thing is, I mean I've talked to a lot of investors about this that I think a lot of folks are in that cycle right between B2B back to the sort of like app layer is a bunch of the investors are pretty interested in obviously the B2B AI side. And I think that will then drive a lot of innovation which then gets you the 10x here and hopefully someone builds a good network. Then you have sort of like unwarranted or really sort of differentiated customer acquisition.

That makes sense. Well, thank you so much for joining. This was fantastic.

Come back. Come on. When there's big game names, of course, of course games correspond. I'm gonna take this hat. Please do it.

Enjoy it.

All right, see you guys.

Let's bring in the next, the next.

Person this guy is.

We are actually eating 2025. Eat data, make chunks. Welcome to the stream. I'm John, nice to meet you. Can you introduce yourself?

My name is Shreyash. I am the co founder of Chunky. Chunky, that's the name of the.

What do you do?

We take really complex documents, split them up into meaningful pieces such that one piece is one idea and then we send your LLM only the data it needs to answer questions.

Give me an example of a really complicated document.

Financial reports. You've got graphs, you've got actual text data, paragraphs, you've got tables.

And if you're asking about these are so annoying because there's like so much boilerplate you need to just skip to the right thing.

Exactly. Yes, exactly. And like most of the time when you're asking questions to an LLM you really only need one table. Or maybe you Need a summary. That's it.

Why don't I just throw all of that in a big context window? Gemini, 1 million tokens or something and then just ask it, what's it?

It'll work with like maybe one PDF, but you have a whole database of PDFs. You've got like hundred page PDFs. Thousands of those. Ten thousands of those. You got schematics which are really complex models get confused. We actually ran this eval yesterday after the price drop on 03, which is we took relatively simple documents, we took classic literature, David Copperfield, Les Roble, everything like that. And we gave that to O3. We asked very pointed questions. O3 got a retrieval accuracy of 75%.

Okay, great.

We chunked the data through chunky. Then we asked Joe 3 the same thing. Always chunk 100%, always chonky 100%, always chunk. This is my favorite name since last YC batch, which was a company called Pig.

I was sending a trend here. You just like large animals.

I mean, so it's just, it's going to stick. We're going to be talking about this next demo day.

Talk about the pipeline. I have a bunch of huge PDFs on S3 or something. I feed it into your system. Am I getting postgres table? Am I getting a mongodb like unstructured?

You get embeddings.

Am I getting embeddings? So it's like a vector database.

Yeah. So you get embeddings out there, you can put it on your own vector database or we can also wrap around your vector database. That's totally up to you.

Okay.

It's really developer friendly. The idea is to just make a dev tool that people just enjoy using using. And they can have it be two lines of code, five lines of code, whatever it is.

So what's actually happening with. It's not open source, Right?

It is open source.

It is open source.

We have an open core strategy.

Okay.

And so we are, we are like open source. First we started as a side project on the open source and we love the open source.

So. So is this something that I should be running like in like an ingest process? As I'm generating new large documents, I'm chunking them and then loading them into my vector database, which I may be also hosting.

Chonk. But if you're building a code gen tool, then you want a live chunk. Yeah.

Okay.

And so if you're doing like Cogen on the fly or if you're like, you know things, if you're working With a corpus that's changing all the time, then you do want to. You want to do it live. You come in. You came into YC with this idea. You already had it as an open source project. Yes, yes, we had an open source project all set up in like February, and we came into YC with this idea.

How many people on the scene?

It's just me and my friend from seventh grade, the boys. Group chat. Made it out of the group chat and then we're not.

How many chunks have you chunked? How many stars do you have on GitHub? How much revenue you making? What do you get? What do you got for us?

Oh, boy.

Quantitative metric side.

So the metrics I really like are We've got over 180,000 downloads.

Very nice.

We've got over 200 projects using us.

Wow.

We're a core dependency on projects like Llama Index.

Oh, cool.

Nice. And we've got like 10 to 12 batch companies using us.

Cool.

Good. Inbound coming in from there on.

Fantastic.

Already done. What was that? Round is almost done. We're trying to wrap it up this week. Thank you. Preliminary, yes, Just. Just weighing our options and just like making sure by Friday it'll be done. Amazing.

Well, good luck out there.

Well, thank you so much. Thank you for having me. Never stop chonking.

Never stop chonking. We'll be following.

What's the domain? Domain C H O N K I E A I. And if you want this merch, it's shop chonky AI.

Oh, he's already selling merch.

He's selling merch.

Let's bring in the next.

Great to meet you.

The next participant of the demo day stream, if we have one.

We got.

Welcome to Demo Day 2025. We are live from Y Combinator in San Francisco. Great to meet you.

Nice to meet you.

I'm John. I'm Cinnamon. Hi, I'm John.

Abhijit. Nice to meet you. Nice to meet you.

Can you introduce yourselves?

Yeah, I'm Cinnamon. I'm a mechanical engineer by background. Built hardware for Apple, Google, Slack.

Wow.

Hardware. Hardware. Hardware for Slack. Yeah, yeah.

What do they have?

Rfxway. Oh, sorry, the Stanford Linear Accelerator Center.

Oh, that. Oh, not slic.

Not slic. K. Okay, that makes more sense. What hardware device did I use? Good. Clarifier. Cool. Awesome. So I'm Abhijit. I worked as research A at Stanford, researcher at Harvard. I was like an intern at Intel.

Cool.

Built a lot of stuff, I guess.

Can you pull up on the mic a little bit more and Then tell us what your company does.

Yeah, so we're Goella. We're building a frontier physics model for mechanical engineers.

Okay.

So currently, AI models can't handle physics accurately because a lot of them are language based.

Yes.

Ours are different. Ours are built to handle physics accurately, which means it can be used as a faster, cheaper replacement to simulations and physical prototypes. This is something that I think a lot of labs like to promise. Right. Solving. You know, it was this idea of solving these problems in physics.

So walk me through it. Sounds like you're actually training a model. Is it all reinforcement learning with verifiable rewards, or are you generating a whole bunch of training data? Is there a human data labeling component? Like, what is the pipeline to create what you're creating?

So at a core, we extract embedded physics from data, and that makes it generalizable. Okay, did you want to share more? So we don't use reinforcement learning or anything. It's basically like this sort of encoding framework where we actually take the mesh itself. We work with meshes. Right. Because we're in simulation and stuff. So we take the fluid mesh and then we encode into this lower dimensional space, and that allows you to learn the actual physics of the system.

Interesting.

And when you do symbolic regression on the latent space, you get a lot of. You get a lot more generalizability than you would get with a regular model. When did you guys start working on this? Did you bring it into YC or did you pivot to this? We brought it into yc. So we were teeing a computational mechanics class together at Stanford, which was teaching undergrads in mechanical engineering how to use the traditional simulation software. Kind of bred a hatred for those softwares. Meanwhile, Abhijit's doing insane research at Stanford to use ML to model the physical world in these crazy accurate ways. He's, like, building ML models for intel that are replacing months of trial and error in their plasma edge process. And I realized, like, hey, there's this huge opportunity to out with the old. Out with these old simulators. Let's bring physics informed ML to the broader group of engineers who could really benefit from these faster, cheaper answers.

Okay. Try and make it a little bit more concrete for me. I'm familiar with, like, cfd, Computational Fluid Dynamics. I have a. I have an engine, and I'm trying to simulate how the air will flow over the jet that I'm building. Is that an example that we. We could use to kind of build off of? Is it just faster inference than calculating everything deterministically? Is that the goal?

Yeah, absolutely. Like all of simulation, every time you start with a simulation tool, the engineer is starting with a question. Right? You've got a question in your 3D model, you want to know what is drag? Yeah, exactly. How is that going to change as I change thickness or angle of attack of my airfoil? Now imagine instead of needing to learn a simulation software, you can ask with natural language, drop in your CAD and get simulation quality results instantly. When we say instantly, it's 4,500 times faster than a benchmarked GPU accelerated solver that we tested against.

Wow. Wow. Okay, very cool. What's the go to market like? I mean imagine you're selling to like very large aerospace defense companies or who else is building stuff? I mean Apple, Google, these companies could buy this.

Yeah, exactly. I think the huge benefit of physics informed ML is we can tackle problems that traditional simulators cannot tackle. Multiphysics, multiscale make it extremely feasible to tackle those problems. And we can also fill in the gaps where your idealized equations don't suffice to capture the complexity of the problem. So these problems that Apple, Google, maybe aerospace are throwing millions at in terms of R and D and building and testing, we can give you accurate physics models that can replace your need to physically build and test a product.

And they can probably like reality check your faster results with the traditional system that they have in place.

Whenever they need to build that confidence, run that overnight instead of design traction, selling it. So far it's been great. So we launched two weeks ago. We entered a 25k a year contract with an engineering firm to replace ansys which is 30 billion dollar incumbent. However, I think our stronger pool right now is we have some exciting opportunities with enterprise customers to again tackle those high sally problems where you don't. There is no solution for, for modeling something like drop simulation.

Right.

Like there is no great simulator that gives you that fast accurate answers even though it's, you know, governed by software. Gets like 70% accuracy or something. Yeah, yeah. It's also very slow though. It's like two weeks to compute a drop simulation on a 14 inch MacBook Pro today. So like these really high value problems for enterprise customers, we have the opportunity to go apply our software and they'll give them more accurate answers.

Very cool. How big is the team? Where are you going next? How's the fundraise going?

Yeah, it's three core, one advisor. The fundraise is going well. We're just about. Well it's very exciting. We're just yeah, yeah, yeah.

Amazing.

Whoever's like, you know, bidding, I'm sure they're, you know, gonna watch this. So congratulations.

Fantastic demo day. We've been giving out hats to folks who come on the stream. Thank you so much.

Thank you so much. Nice to meet you guys. Congratulations.

We will talk to you soon. Yeah, let's bring in the next team or whoever it is. And we got don't forget to go to vanta.com adio.com numeralhq.com, adquick.com 8sleep.com Wander.

Go to every website right there.

Look at the bottom bar.

What's going on, guys?

Hey, how you doing?

Dan, what's happening?

Good to have you on the stream.

Nice to meet you.

Welcome to the show. Can you introduce yourself for the stream?

I'm Linus.

Linus, Pleasure.

It is a pleasure. Do you want me to go into any more detail?

Sure. Let's get Justin's name.

My name's Justin.

And what do you guys building?

We're building Den.

Okay, what is Den?

Den is cursor for knowledge workers.

Okay, so break it down.

We're an AI native. Slack replacement. If you, if you load up to the app, you'll see a bunch of AI agents.

Slack replacement.

Slack replacement.

Okay, so I, I'm not in Slack at all. I'm just in Den when I'm doing knowledge work. Okay, what is the typical knowledge worker like experience with Slack? Because I feel like there's a lot of just like managerial overhead status updates that are going on. This sounds like something a little bit more mature than that. What. What am I doing in Den?

In Slack, there's a lot of kind of lost threads, kind of lost information and just a lot of communication ultimately, but no actions. With Den, we're all about actions and we work backwards from what you need to get the task done.

So give me an example.

Yeah. So I guess in Slack you would be asking your coworker for how many users signed up last month. That's going to be like an async.

Process where it literally just happened in the Slack. In one of my Slack. I mean, it's like, are we reviewing last week's numbers or the week before or the week before? Was a developer on a team talking to the CEO? Yeah, sure.

You know, in Slack that task might just get lost in the background. You don't know what the status is in Den. And AI agents just going to pick that up. So, you know, we're all about like that multiplayer aspect. Your inputs are building the agents and kind of configuring your tools and configuring the tasks. And then we kind of provide like the multiplayer in environment where you might be orchestrating like thousands of AI agents.

Yeah, talk about the path of AI agents. Long running agents. We have this idea of like 10 minute AGI, 20 minute AGI. O3 Pro seems to work for 13 minutes every time you kick something off. Are you putting these things on cron jobs? Is there some sort of like long running process that can run through my den installation and say, hey, like every single hour I want you to check on things that aren't getting done run.

Pretty much. We break it down into three things. Like you've got your ad hoc tasks, you've got your cron job task, your scheduled tasks, and then you also have things that kind of respond to triggers. It's like, oh, hey, run this task whenever I receive an email.

Got it. Okay.

There was this idea, I think it was in AI 2027, around the idea that an AI would just spin up a Slack instance and use that AI.

Would use Slack to coordinate with each other.

And I can see a world where that makes sense. Sense. What was the catalyst for you guys to realize that you needed to kind of rethink the communication stack from the ground up to serve agents over, you know, first and foremost over humans. I guess what we realized was that there's tools like zapier tools like relevance AI, but they're external to your communication source. Knowledge workers spend more than 80% of their time in Slack and Notion. And so we wanted to bring the agents to where people actually did the work. And the most important thing is now the agents can escalate tasks through like the CEO, the head of customer success, whereas they couldn't before because they were siloed. So we had to build it from the ground up for agents in that way. Do you think we'll still call ourselves knowledge workers in 10 years if knowledge is instantly accessible by all machines?

Taste workers. There will be taste workers and agent when agency workers, because knowledge is commoditized now and intelligence is too cheap to meter.

Like taste curators.

Yeah, exactly. Taste makers. That's the only job that will remain in the future. Maybe.

Who knows how you guys are creating a platform that other agents can work on top of. How do you rank, how do you rank the quality of different agents across categories? Obviously there's like coding agents. We're friends with the Cognition team and the factory AI team and things like that. So coding agents are great. I haven't Heard a lot of people saying, like, I love my AI BDR yet.

Right.

Maybe there's some use cases, maybe they don't want to talk about it. But what are the categories that you guys are most excited about? Yeah, deep research is obviously another category, but I think it's going to slowly move down like the stack. I spoke with Sholto Douglas, who is a researcher at ant.

We had him on the show recently.

We have great coding agents and kind of math agents because researchers like math and coding.

Interesting. But it's not just the verifiable reward thing.

It's that as well.

Okay, that as well. Yeah.

I think we're kind of building in the infrastructure that's going to allow those like iterations to happen where you do actually get like a really good BDR agent. We're already building customer success agents that haven't existed before because we're providing like the primitives and the building blocks and I think the verifiability will come. It's just interesting.

How's the traction been? What's the rollout with the Go to Market?

Go to Market is handing out 500 business cards. Yes. To everyone at Demo day.

So you want every company here, all the small startups, the early stage companies. That feels easier than ripping out some massive slack installation, right?

Exactly. Okay. We take a lot of inspiration.

Start with Dan, stay with Dan forever.

Exactly.

Okay. Seat based pricing.

Yes.

Interesting.

Agent based pricing.

Yeah. Do the agents have to pay? What if I have a thousand agents? Okay, so the one person company, you're. You're cooked.

Exactly.

Good luck though. You'll figure it out. I'm sure, I'm sure it'll be fine.

Have you shared before this?

Yeah, yeah.

I previously started a company when I was 19. We grew to like 0 to 5 million ARR. 50 people.

Congratulations.

Thank you. You know, start this three months ago now. So it's been awesome.

Awesome. Very cool. Three months right before yc.

Exactly.

Yeah.

Justin, what were you doing? Yeah, I mean, Linus is a beast. He hired me actually at his previous startup. So I was able to kind of go from like that 500 to 5 million.

Yeah, yeah.

And we just loved working together.

That's awesome.

This is what we wanted to spend the next 20 years on.

Yeah, yeah.

Amazing. Wow.

Fantastic. Thanks so much for hopping on the stream. This was fantastic. Good luck, guys. See you on the next one. And we are ready for our next guest. Coming on in to the palace of party rounds to YC demo day 2025. Welcome.

Eloquent.

How are you? Doing.

Nice to meet you. Very nice to meet you.

I'm joking.

Hey, Jordan.

Nice to meet you. I'm John. Pleasure.

What's happening?

I'm kicking this over. Would you mind starting with an introduction on yourselves and the company you're building today?

Absolutely. This is Tuche. I'm the CEO of Eloquent AI. And I'm Aldo. I'm the Chief AI Officer of Eloquent AI.

Fantastic. And what are you building?

We are basically building an AI platform for financial services to automate complex regulated operations.

What's an example of that?

For example, in a bank, if you want to unfreeze an account or handle a reggae dispute, run Kyc Kyb. Sure. This usually goes currently to support teams and you have a big queue. Right. It might take up to two weeks to open a new business account.

Happens all the time.

So we solve that problem rather than that going to support team. It comes to our dedicated AI operator.

Sure.

Our AI operator takes on the job and here's the real magic. It basically navigates your existing core banking portal just like your support team does. We don't need any APIs or any engineering. Exactly. Right. So this is coming from Aldous Research. For more than five years they developed this technology that allows us to do computer use and browser use in a reliable way for very specific tasks.

How much of what you're doing is purely enabled by the advances that the foundation model labs versus fine tuning or any sort of scaffolding that you're doing on top of the state of the art models?

That's a fantastic question. Do you want a little. Yeah, of course. It's a little bit of both. Right. Foundation model of course, gives us a lot of synthetic data for which we can. On which we can train on.

Sure.

But you know, we left leverage multi agentic architecture to actually perform the actions reliably.

What's the response been from big regulated financial institutions? They are not traditionally the earliest adopters of new technologies. But everyone's talking about AI every day. So I'm sure they're excited to at least talk to you. What's the response?

You know, things have changed. We are finding it. Actually. We reached half a million ARR in four weeks.

Congratulations.

I love that. And the reason is because I think all these banks now have the mandate. Wait, did you say four and a half a millionaire in four weeks?

There we go. All right.

Just do that every four weeks for the rest of the year. Well, at this stage we actually have a waiting list. We have more customers than we can onboard. Because As I was saying, things changed in the financial industry.

Industry.

They want to bring this cutting edge AI in house as quickly as possible.

That's amazing. Very cool.

How's YC been? Honestly, in any metric, it's massively exceeded my expectations. Amazing. I'm a second time founder so I thought, okay, do we really need to come to yc? You know, we already have the investor networks but what was really beyond my expectations is the customer network, especially in financial institutions. Institutions is incredible. A lot of YC alumni are now running big fintech companies, banks and they have been very welcoming. We can definitely feel the love. That's amazing.

Amazing. How big is the team? Where are you going next? I'm sure you're raising money. What's happening down the. Down the road? What's in the next 12 months?

Absolutely. So we raised a big seed round. We closed last week. Congratulations.

That's a big one.

We close the seed round, everyone. I love that. I love the spirit here. That's amazing. That still surprises me every time.

Yeah, it does.

It does still surprise me. I love it. And yeah, we close the seed round.

Congratulations.

At the moment, it's basically heads down. We are building.

We are six people.

Aldo is leading our technical team.

Fantastic.

I do sales. We are hiring 10 more people. So anyone is watching who is looking for a new role, they are very welcome to contact us. That's amazing.

Well, thank you so much for stopping. Let's bring in the next guests. We are live from YC Demo Day 2025. Book a wander.

Find your happy place. Find your happy place.

Bring about it. Go to wander.com.

Hey guys.

Welcome to the stream. How you doing?

Good.

Good to meet you. How you doing? Good to meet you.

Good to meet you.

Why don't you kick us off with an introduction on yourselves and the company you're building?

Sure. I'm Somi. And I'm Achut and we're building ulearn. It's an AI tutor for students.

Very cool. What's the go to market? I tried to build an ed tech company back in 2012. That was actually the first company I applied to YC for. It was a disaster. It was extremely hard. Never really like made a dime off of it. I think I got like 500 installs on the iOS app I built.

Let's get 500.

Yeah, yeah, yeah. Not exactly one of these. How are you solving that? Like, it's notoriously hard to sell into.

It is.

But into education.

We're seeing a change, especially with AI.

Yeah.

We have over 200,000 students activating website. There we go.

A thousand more than what I got during my YC day.

Thank you. Thank you.

You got so many guys can keep talking. Okay. $200,000. We love it. So. Well, what is the channel? Is it.

Let me guess, you got a bunch of tik toks. We have, I think over 500,000 followers on Instagram. And how.

How long.

We project for a while, But I think 18 months is like. Like for the past few.

Eight. Okay.

And how do you. I'm picturing kind of like an LLM style chat interface. Is that the wrong. Yeah. So essentially, like, students upload their, like, learning material, like textbooks, and we give them like concise notes.

Sure.

Like you can have a conversation with an AI tutor.

Sure.

Like you can have quizzes, you can create exams. All the study tools you create, like podcasts based on. Yeah. So right now it's a conversational experience. We want to make it, like more proactive, active.

So. Yeah. So you can listen. Yeah.

And are you getting to the point where teachers and schools are kind of asking their students to get on the platform and use it? Yeah. So we're talking to a bunch of school districts and stuff, but I think our main focus for now, students, we just want to, like, get the product down for them and then. And what, what, what, what level are we talking? Middle school. Yeah.

Where's the option been strongest?

Yeah. So undergrads are like number one right now. And then it's higher than that. And now we're seeing a lot of high schoolers as well.

How are you? Are you monetizing it?

Yeah. So we have a freemium subscription. It's free for like a limited amount of time. And then 20 bucks a month.

20 bucks a month.

I have an idea. Search based pricing. Exam right before exam fees. Yeah. We give a discount on exam season. And that worked really.

It worked really well.

Even post exam, like, there's always a summer sale. Yeah. I think it just works out really well.

That's amazing. Wait, so how long have you actually been building this? I missed.

So we started eight months ago.

Eight months ago. And then yc. Okay, great. So have you been focusing on specific growth metrics during YC to kick off demo day?

Yes.

Just growing everything.

Yeah. So MRR is like our key metric.

Fantastic.

And then retention as well. We want to make sure, like, like a key part in learning is like retaining.

Fantastic. Did you share an MRR number today?

Yes.

Can you share anything with us?

Yes, we can.

Fantastic. Let's hear it.

We are at $75,000.

Let's go. Congratulations.

I mean, honestly, I gotta say sorry, cuz. Just.

Yeah, I know.

83.

83 would have been 1 million.

You're close. Yeah, you're close. Next week, put another sale on Go to every person in the B. Every.

Subscribe right now. Subscribe right now.

Let's get him to one mil. Let's get him to one mill.

Fantastic.

You actually. We're not gonna let you leave till you get to a million. Okay. Okay.

You got to stay in this room. Last question. Obviously, tons of developments from all the foundation model labs. What's working? What's most exciting? What are you taking advantage of? Are you focused on cost optimization? Looking for open source? Do you want to use the best? Are you a beneficiary of the O3 pricing drop? Are you a beneficiary of O3 Pro?

100%. Every model improvement benefits us directly. Yeah. We want to focus on accuracy the most right now. You want to make sure everything that a student gets is as accurate as possible. Are students cooked by AI leveraging it more just to study smarter? And that's what our vision is. And also an interesting thing is they really like our voice mode.

Yeah.

So it's not just text based. They can have a, you know, like a natural conversation. Yeah. So is it like you leave it open on your desk when you're studying? Yeah, can do that. Yeah. And it can, like, create mind maps for you. It can create, like, flowcharts. You can create whatever you want.

Very cool.

Yeah.

How are you seeing the. The. The. The competition?

You guys drop out in the process.

In the process.

Legally.

Legally.

Not yet school for you, but not for me.

How are you seeing, like, the obvious competition between just like using chat GBT, 20 bucks a month. That's right at the pro tier or like the. The plus tier here? There's a lot of Tyler Cowen's been writing about. I used to feed in a snippet from a book and ask ChatGPT about it. Now I just say, hey, summarize this book and it already knows. Or you can just go out and find it. That feels like the logical competitor. But how are you differentiating in terms of actual UI design? Because it seems like as we move to the application layer narrative, there is a world where aggregates segregating demand around AI tools around a specific niche works. But there's a lot of secret sauce that goes into the ui. What are you doing to stay ahead?

So, yes, definitely a UI is a big component, but the main thing Is we just asked our users why do they use us or ChatGPT.

Sure.

And they say like we have like a feature called the quizzes flashcards and we create that like very accurately for them.

Interesting.

And what they can do is they can upload like a thousand page textbook, even 2000 page. Someone uploaded like the entire Imagine Imagine hallucinates and you just fail your exam.

So I remember in college I had a textbook and I wanted a digital version. I took it to a scanning and they scanned it all and they were like, do you have the right to do this? This sounds illegal. I would try and download illegal PDFs. It was very sketchy. How are college students uploading 2,000 page documents?

Yeah. So if it's available digitally, they can upload it.

Okay. Like mob.

Yeah. So I mean they can upload anything they want, but it's on them.

Okay. Okay. Yeah, they have to figure out that part of it. Okay, got it. But eventually maybe you could do partnerships with.

Oh yeah, we want to like partner with like ebook.

That'd be very, very cool. Amazing. Well, congratulations.

Yeah, thank you so much.

Later. And let's bring in the next team.

Let's do it.

Lightning round. Let's speed these up. Right, Speed these up. There's demand. Is there demand out there? Okay. Okay. We only have two seats.

One of you can take me. Oh my God.

Come in, come in, come in. Okay, realistically, only one of you or two of you can talk because there's only so many mics. Keep going. Can you guys move the camera to show everyone for a second? Just tilt that camera. Look at this army. Yeah, yeah, Tilt over a little bit. Go to the wide. I want to show these guys.

Are you guys, Is this the founding team or all the founding teams? World record. Who's a founding engineer? There's one guy who comes.

There's one guy.

Legend.

What are you building? Break it down for us.

So we are building AWS for AI agents. Like imagine we are. 20 years ago, it was mostly infrastructure for software as a service. Now AI agents are becoming like the de facto new software.

So we are building this infrastructure for the. What is, what is important about infrastructure? That needs to be different. Why would I not just deploy this on AWS or Microsoft? I mean, you saw Satya Nadella at Build. He was saying like, we have model router. We have everything from deep seq to lama to they vend every model. How are you going to stand out?

Yeah, we stand out because today, first, people who are building agents are not cloud architect. Cloud you know, infrastructure experts. So a new generation of.

Of software developers, software engineers.

Second thing is agents are going to.

Build themselves their infrastructure.

So they need new interfaces to interact with the infrastructure and the type of.

Workload that they are using, like the.

Technology they are using. The lifetime of the computing platform is not the same. So serverless is one thing.

Traditional virtual machine even going back to the YC story. Heroku.

Yeah, exactly.

It was that story of like yes, you could always spin up EC2, but Heroku made it easier.

Exactly. And right now we are doing the same for agents. So when your agent is generating code, it needs to have access to some resources to run this code. So we provide these kind of resources.

Called sandboxes to help them to run.

This code for 15 minutes, an hour.

Or maybe months or years.

How did you. When did you show up the company? Did you. Did you start three months ago when YC started or you guys have been at it for a little bit? Yeah, so actually we both all worked.

In my previous company.

We sold to a cloud provider. So we. We know the traders hate over here.

It's like intel again. What happened? Retain any of you? You couldn't be bought. I see what happened.

No, it's the six of us. Amazing.

Congratulations. You guys stick together. I love it.

I love it.

How is adoption been? Who are you selling to? Who loves this product?

So we launched, we launched several weeks ago and like most of Guardian Narration companies from these batch, even in the.

Next batch are starting using us really.

Ready paying customers in production right now.

The economic model, I assume it's consumption based on top of the underlying cloud platforms that you're building on top of, is that correct?

Yeah, exactly. We started actually to do something with a unique subscription, with monthly subscription just.

To be sure that people were serious about using us.

Being sure that we get the right traction. Like they are using actually in production our software. Now we want to expand so we are basically offering more just a usage.

Based model for the next batch.

You guys live in the office. So we leave.

We sleep when we can sleep.

You have.

But we live in that office. It's a lot of mouths to feed. Have you raised money? Yeah.

Rounds close.

Congratulations.

Thank you.

Congratul. I think Jordy's got some for you.

Spray them all with it.

Spray them all. Fantastic. Well, congratulations.

Thank you so much.

Thank you so much.

Thank you.

Fantastic team. Look forward to following your journey.

We got a.

A great. Have a great time.

Thank you.

Bye.

We got a good name coming in next. We got waffle coming. Let's bring in waffle Waffle.

Come on in to the palace. Party rounds. Oh yeah, they're customer. That's good.

Customer. Love it.

Grab some seats. Put the microphones as close to your face as you can because we are live from YC 2025.

Building agents for agents.

What are you building?

We're building an AI operating system for small to medium businesses.

Okay.

So what that means is we help you build your website, set up your business email address, your phone number, your bookings, your payments, all that kind of stuff. Are you guys replacing Google Workspace? We're starting building on top of it. We're starting off replacing Wix. So we've just, we've just launched our AI website builder three weeks ago. We've had 700 projects built on there. And yeah, people are building websites.

Okay. So you build the websites and then you also are able to instantiate all the downstream stuff. But I imagine you're not rebuilding everything. So who are you plugging into? Like you're not rebuilding Stripe, right?

No, we're not rebuilding Stripe. It's like wrapping on top of these developer tools.

There's so many of them now.

There's so many. And they're so cheap.

Yes.

You know, like if, let's take just like outbound email marketing.

Yeah.

Someone could use something like mailchimp.

Mailchimp.

Yeah. And that's much more expensive than how much me and Diego pay when we set up a project with resend. Because it's a developer tool, it's super cheap.

Interesting.

And then we can make money on the spread.

Okay, interesting. How's adoption been?

Adoption has been really interesting these first few weeks because we've done no marketing mean we're just like full time coding, working on the product. So we've had people come in from the YC launch from the Twitter and now in the, in the coming months, what we're doing is like going in and doing more go to market stuff. So one of the things we're doing is taking people's existing WIX or Squarespace website and just cloning it, putting it.

To Waffle and then just sending it to them.

Sending it to them.

I've seen a lot of WIX and Squarespace. You see the web, you see the ads, the super bowl ads, and it's always a small business, a restaurant or a pub. And do you have a couple customer avatars that you really like or want to use to fuel your go to market?

Yeah. Right now I think what's really interesting is like these small family run Businesses like these small family run travel agents or law firms. I think long term term E commerce is really where it's at. They care a lot more about their website.

Yeah, yeah, yeah. How important is design in that? Are agents good at design yet it doesn't seem like it's something that would come native and yet the. A lot of the AI art that's being produced is beautiful.

Yeah, yeah. I mean yeah. It's interesting. The default clothes like if you just ask lo to generate some ui, it's actually quite good. But it's very unopinionated, unopened.

Opinion is generic.

Yeah, it's just like some gener generic type website.

Sure.

I think if you start giving examples and just really working the system prom you can get it to a point which is pretty good. What we've been doing is using 21st dev.

It's a, it's a tool.

They have a lot of UI and they're building out their magic chat which.

Allows you to kind of take a.

UI components and like have remixes of it.

Very cool.

So that they're work on that specific technology and we're working with them. So yeah, it's actually pretty good IUI but it's making stuff which is still quite generic and we're trying to push the boundary. What were you guys doing before this? Yeah, so we've never worked full time jobs neither. Let's give it up for unemployment. You guys are founders? Yeah. Yeah. So we, we, we both did computer science. I was at Oxford, Diego was at Ecole Polytechnique Lausanne. Met up in London.

Yeah.

Moved in with him and then we've just been working.

We got you too. It was impossible to build a company in Europe and you're testament to the fact that you gotta come to America. Congratulations.

Yeah, it's been insane. I was listening to you guys two days ago.

Oh really?

And when the Cluley founder was on and now we're here.

Yeah, it's important to get attention, but there is a limit. That's our message.

Where's the line for you clearly has their line around what they're willing to do for attention. Pretty crazy, you know, willing to go that way. YC goes the other end of the spectrum where they're like just don't focus on your pitch. Let the numbers speak for you.

Yes, yes.

And they're like just put your graph up and that's what matters.

I think it's good. Did you have a number that you shared today?

Yeah, yeah. So we got 700 projects built in the last three weeks and then that's grown 14 over the last week.

Congratulations. We're good luck with the rest of demoday. We have one last hat here. There might be more out there. Share that based on days there's more hats. Let's give them two hats. Are we out of hats?

Yeah, we don't want to run anyway.

Congratulations. Let's bring in the next team and let's tell you about Linear Linear app use to manage your projects.

At least half the badges I think.

So welcome to the stream. How you doing?

And water. I'm going to not shake your hand.

Good to meet you. Let's start with an introduction. Who are you guys? What are you guys building? And please microphone as close to this as possible.

Yeah, I'm Daniel Cool. And this is Moussa Cool. We're the co founders of Vibe Grade.

What do you guys do?

So we help teachers save time grading papers directly in their existing learning management system.

What's the response been like? Do the teachers love it?

Yeah, actually all of our customers are paying out of pocket.

Really? Wow. Okay. Interesting. You said in their lms.

Yes.

So who are you plugging into? Who's the most dominant platform providers right now?

So the main one, the best integration is on Google Classroom.

Oh, interesting. So a lot of black is blackboard not a thing anymore.

Not that much. We got a request for it but most teachers are on Google Docs and Canvas.

Sure.

So like most K to 12 which we serve are on Google Docs in classroom.

Yeah.

We have Toddle as well. But it's mainly those few. Makes sense. Yeah. But for universities they like Canvas is great. Like they can. It'll go and highlight actual sections.

So can you add that on as like one of those like if I'm in Google Docs I can. I can do an add on extension. It's a Chrome extension.

Yeah.

Okay.

So we realized that teachers, they don't want to have to learn a new tool.

Totally.

And go to a new platform to do that. So we built an integration that works directly with Google Docs and directly with Canvas. So it's easy as clicking a button and then we open up a window. Window inside Google Docs.

Yes. Walk me through the typical like workflow homework. I. Yeah. It's like the student uses the.

The teacher.

Daniel was just to write the questions.

Yeah.

The student uses ChatGPT to write the answers and then the teacher goes back and you guys, you guys grade it.

Yeah. But.

But what's the actual workflow? Are students sending Google Docs links to their Teachers when they're done.

So. So Daniel was just in high school, so he really knows how this works. Yeah.

You dropped out of high school. Get the bottle of wine. Congratulations.

Yeah, yeah. High school dropout. So the word chat. Yeah, yeah. He front ran everybody. Everybody. That was like coming into demo day.

Oh yeah, I dropped out of college. It's like that's how it played out.

You had to one. Yeah.

To go farther.

Yeah. I mean you're selling, I think we heard about you earlier. You're selling it back to your teachers now like that you dropped out of sort of. I mean they don't really like me that much for some reason. Yeah. Like on my final exam. Well, I mean I skipped finals to go fly to. We went to this EdTech conference in Orlando. So I guess they don't really like me because of that. But we, we had to bring in some more teachers.

They'll like you when you're the commencement speaker in a couple years maybe. Yeah, hopefully.

So the workflow is where teachers, usually the students submit on Google Classroom or like Canvas. They submit a Google Doc or a PDF and then the teacher opens it up, the doc, and they grade it within by like highlighting certain sections, adding comments, comments, a summary of the feedback. So we do that whole process right in the Google Doc and then we have the teacher review everything they can speak to our system to understand their tone and their style. So then we add those comments.

How, how is the actual like testing and grading and homework process changing? Because I imagine that the like the solution to ChatGPT homework is probably everyone's on a laptop typing the answers in the classroom and there's a monitor watching that. You're not just AI ing it and then it can be AI graded and then that's a win for everyone. Is that roughly what's happening?

Yeah, like the thing that we've seen is like people say all the time, you know, like students are writing with ChatGPT, teachers are going to grade with AI. Like what's the whole point? But, well, the objective of the student is to learn. And if you're just using ChatGPT and mindlessly submitting something, well then you're not doing the right thing. There's always going to be a way to get around it if you really don't want to learn. But for teachers, the main objective is to give students the best feedback and instruction. So what we're doing is just enabling them to do that a lot better. Because even in school when our teachers would give us just generic copy paste feedback so we just want to give students the best feedback possible. Gives teachers their time back and they really get the value because they're the ones experiencing the benefits.

Yeah. Talk to me about the top of.

Why would you not at one point just give the tool to students? Yeah, as well. Yeah, 100%. That's actually what we're working on next. So we just signed three contracts with schools last week.

Okay, congratulations.

And they want to be able to give this tool to students so that while they're writing they're going to get get real time feedback on their Google Doc as if the teacher were adding comments in real time. So it's sort of like, you know, you submit a rough draft to your teacher, they have to grade it and then give it back to you and then you can do a final draft. Instead of that, why not just have like the assistant give you feedback in real time?

Oh yeah, that makes sense on the doc. Yeah, that's great. Talk to me about the top of Funnel. How are you telling teachers that this works? I imagine at the price point you can't do hand to hand combat sales. How are you getting in front of teachers these days?

So all of like we have 100 teachers that are paying completely out of pocket and all of that has been organic through either the Chrome web store. So they find us when they install another extension. Like Grammarly.

Yep.

And then they tell their friends about it. So word of mouth has been really Strong. We got 600,000 views on Instagram and Facebook in the past 30 days.

There we go.

We just started posting like memes and things like that. And teachers really? Yeah, they share it and then they look at our page and so they find us there.

That's great.

So that's the top of Funnel up until this point. And we're gonna start pumping out more like UGC style content. We're actually going to the biggest edtech conference in the U.S. let's go. @ the end of this month.

The super bowl of ed tech.

Yeah, there's 20,000 teachers there and we got a really big. We bought a 400 square foot booth there and we're going all out for trying to reach as many teachers as possible.

Congratulations.

How did you guys make your first money on the Internet? Thank you. How did we first make. I used to make, I used to make websites for like random people. I charged like this pastor in New Jersey like $3,000 to make his church a website. Wow. There that was back when I was maybe 16. I made like a, a mental health chat app in like grade 10.

Nice.

And like a couple of people, like one person in Japan found it and they installed it and paid for it.

They paid for it.

Let's go.

That, that's amazing. Congratulations. Really rooting for High school's cooked.

Excited.

Call us when you meet the first. Yeah, we're good.

We got middle school dropout.

Middle school dropout. That's where I was going with that. Welcome to the stream. We are live from YC Demo Day 2025. Good to meet you. I'm John. Nice to meet you. Welcome to the stream. How you doing? We're gonna have you sit down here. We're gonna have you pull this microphone as close as you can, talk directly into it. Introduce your company. What do you do?

We are building agents for insurance claims operations.

Okay, how is that going? Are you. Is business ripping?

Yeah, we're 200k now.

Let's go where the money is. That's why people rob banks, because that's where the money is.

Right.

Go to the insurance industry. It's expensive. Who, who are you selling to? Are there. Is it as I assume that the insurance industry is very oligopolistic. There's a few big players, but is that not right?

We're selling to third party administrators which are these like claims outsourcing companies of which there is a surprising.

There's a number of.

Yeah, it's like 42000 across Europe. When did you realize that you guys loved insurance? I wanted to process claims. No, I'd seen it in my job before. Like sort of had some exposure. My roommate is an insurance adjuster so.

I was like interesting.

Look over his shoulder.

Put you had a job so you can hang out and go to more movies on the weekends. I like you working late. I want to play get video games with you. That's the best. Awesome. So yeah, walk me through what you're actually building, what the product experience is like how it plugs in. I assume this is some sort of like co pilot experience right now or is it fully agentic? It's a.

It's a full fully agentic experience. So the goal is to replace like autonomously parts of the workflow for the adjuster. So the thing we're live with with our customers is like a claim intake agent. So when you crash your car and you call in you basically ask you a set of structured questions and then create structured data and writes it into the system of record.

Got it. Okay. And. And previously that was handled with someone on the phone talking and typing everything in.

My roommate, your Roommate.

There you go.

Did you get him as a customer yet? No, not yet. He. He works for a very big carrier, so that's going to be a longer. Playing the long game with that one.

Yeah, yeah, yeah.

And what were you doing before for. I was doing product consulting and then worked as a software engineer at Agentive, which is another YC startup.

Oh, very cool. How's the round coming together?

What's it like yesterday?

Closed it yesterday. Congratulations. Well, thank you so much for hopping on. Good luck.

Thanks. Good luck with everything.

We are.

Congratulations.

We're moving into lightning rounds. I'm gonna give you one of these. Let's bring in the next team. We're moving through these quicker. Thank you so much for hopping on. We are live from YC Demo Day 2025. Welcome to the stream. Come on, sit down. What do we got?

Text AI.

Text AI. That's a good domain. Are we supposed to suit up for this?

No, no, of course. We don't have the right gear. Pleasure. Pleasure.

How you doing? Sorry we don't have an extra chair.

I, I briefly. I caught like 30 seconds. Okay, two minute pitch.

Give it to us again. Well, what's the pitch today?

Yeah, we're AI agent. Right. In your group chat.

Okay. In the group chat.

Yes, sir.

How are you plugging in? Because I feel like imessage. They really don't like when other Companies plug in 100%.

We're carrier based.

Okay.

As long as you have a number that you can just add to a group chat instantly.

Yeah.

Right then and there.

Are you a beneficiary of the RCS update?

Yes, we are.

We are. How?

Yeah, we're working through a couple of providers that give us a number so all working with all the carriers like. Right. And T Mobile, AT and T. And then we're applying for the rcs. It's still in the beta stages even though it's rolled out. But SMS infrastructure is one of the best infrastructure in the world, so that's working.

Whoa, hot take. I feel like everyone's annoyed by it. That's why Twilio exists. But you know, is it, is it good now? It feel like it was terrible for a long time.

I feel like the big question around adding an AI to your group chat is security. Security, things that happen in, you know.

Yeah. Signal group chats. You don't. You want to be very careful about who you are.

Yeah, yeah, we've seen journalists.

How are you handling security?

Yeah, no, great question guys. It's. We don't sell your data. You can Kick out the AI whenever you don't want it. Right. You bring it in, bring it out. Nothing compared to like meta AI where it's always living in there ambiently, it's completely under your control. So we don't sell any of that data either.

What's the, what's the most obvious use case? Like the family group chat, Creating a grocery list or something like. Give me some examples of how people are using this.

It's. It's actually, actually a lot of friends using this to get a restaurant, recommendations, roasting each other. Okay, when do we need to actually all meet up, have reminders in there? That's our first agent. Yeah. Because in, in when you're planning trips and trying to go out, there's always that one person. It's like, no, I'm too busy or this doesn't work for me. And someone has to put in the screenshot. Someone's always taking the lead.

Simplified of adding agents to group things. It feels like, like I saw this meme that was like I joined a Zoom call and it was seven AI agents. Do you see this one? Everyone? Yeah, everyone know. And it was like the one poor girl. And then like this person's no taker. And Fireflies and Lou. And this one and this one. This one.

How are you thinking about building the agents yourself, letting people build on top of text AI? I think two things. Number one is like the quality control that has to come in along the things like you said on the data piece, we, we're a consumer company. We're like text AI, people interacting. You want to be very careful of allowing third parties to come in here and see what they do with the data that's prevalent. And second is like we build it ourselves so we can really figure out specific use cases like calendaring, for example, working with other people's calendars, giving you a exact answer like, hey, between all five of us, when's the best time where we can actually grab coffee later this evening?

Yeah.

And it can actually find it done and dusted right then and there.

How much of the go to market is just pure viral growth? Because someone gets added, you realize that it's text AI and you add it to the next group chat and it just kind of goes.

Can you add a studio Ghibli machine to the group chat? That is a great question. We have Ghibli images working. I wish I can put it on live stream right now, but we actually have collaborative AI where we can actually start doing images.

People can edit it together. I mean that was the beauty of mid journey is that they use discord. Right. And then so if Jordy writes a great prompt I can kind of spin off that makes sense. That would happen in imessage and everywhere.

There's so many fun and I'm, I'm already thinking, thinking like anytime somebody shares any photo just immediately make it like a Star Trooper version of that.

That's like half of our group chat is like somebody just be sending ghiblies of all the other guys in the chat. It's great. Isn't it exhausting that everyone like cuts and pages.

Yeah, yeah.

You go back and forth, back and forth, back and forth. Make it so that everyone is accessing it equally. Yeah, yeah, yeah, yeah, yeah.

And the beauty is you can create an image, he can edit it and someone else can edit it on top of.

Yeah. Much more collaborative.

There is no need to really copy paste images.

A fun use case that I saw just developing this is the best part of being consumer, right. Is that you get to put this out there and you're gonna see what people do. It hinge dates. No. Someone goes in, brings them into a text thread, says hey by the way I have my AI staff here. Digital stuff. Yeah. Do you have any restrictions? Do you have any favorite restaurants? Imagine like this is well above beyond use cases you could have imagined. Yeah, yeah. It's going to place places where people are being really thoughtful about how do you bring it in to make it more easy for us to have a human connection.

What were you guys doing before this? So I was at Tesla for four years leading there. Can you explain what Tesla is? No idea. Your guess as best as mine. No, I was leading the digital supercharging team there and the vehicle subscriptions team.

That's great.

And then yeah, I was leading an engineering team at Walmart and then before that I used to give it up for big. Let's give it up for big retail. Can you explain what docs I wonder what Walmart is. Huh. But before that I was at Eventbrite and OpenTable doing a lot of consumer personalization. So that's why I think one of the main reasons we founded Text AI was our rich sort of consumer background.

Yeah. So yeah, yeah, no, I've had a blast of being in media for a long time. Most recently I was the CEO of a B2B media company down in Los Angeles.

We exited it.

I sold it over in October. Cool. I've not done these guys for eight years. Yeah, she's first job was at a crypto startup my wife was at, no way hired him. And then he wouldn't. She wouldn't leave. He wouldn't leave our house. He just, like, showed up. And so I've seen him do everything. And then for hor. Of course, these guys went to school together. And so the opportunity after going in and doing a lot of executive jobs at, like, publicly traded companies and whatnot, I think if you want to know what's happening, you got to get hands on keyboard y. There's no talk the executive talk and pretend like you. You understand it. You got to get back on. And so for me, this was a great opportunity to go work with these two guys and start from scratch and just get to know what's happening, because.

This is going to be the platform.

For the next 15 years. That's amazing. Well, congrats.

Thank you very much.

Question.

How. How's the watch game at in your guys batch? I see. I see you guys each the Texas time. He has a better g. He's leading the way.

I might be the oldest founder ever to go through YC and so.

Yeah, what are you, like 32?

Oh, yes.

Yes. Lucky guest.

I'm gonna stay with that.

Yeah. Closer to 50 than I am to 32. Okay. Okay. Okay. Well, cool. Pleasure. Pleasure.

Thank you. We'll see you soon.

Bye.

Up next, we have another team coming into studio. Welcome. Good to see you.

Great energy.

Come on. Welcome to YC demo day. I see two sweatshirts.

Pull the mic up.

What is that? Why?

Preliminary.

Preliminary. They're blowing out their metrics. Good to meet you. Can you kick us off with an introduction on you and the company that you're building today?

Hey, guys.

We're.

We're building value mate. We're automating real estate appraisals.

Okay.

With AI. When did you realize you wanted to evaluate real estate appraisals? Yeah, so a little bit, you know, family background, like, things are the sort we kind of discover this pain point. We both study at CMU who have families had a background in it and, you know, seeing appraisals and things of this sort, super inefficient process. And we were like, it's one of those industries just perfect. Like, just ready, you know, to, you know, to become a lot more efficient. And that's kind of how we. How we got into the space. What is the. What is the structure of the legacy market today? There's. You guys are providing a tool for people that do appraising.

Yeah, exactly.

So, like, the current. Like the current competition is literally existed for 40 years. Right. And it's just like, like appraisal reports is like a snapshot of like a property.

Human goes in and looks at things, pictures and writes down a lot of quality. Exactly. Scoreboards and mold.

So we bring this entire thing down and just a scan.

Okay, Right.

So you scan it. We build a 3D model, 2D floor plan, a computer vision, takes notes.

Sure.

And then we pull data from all these various sources.

Got it.

Right. And then, you know, we use AI to obviously fill out this kind of report. So it's a, you know, it's a pretty time consuming process that we're about to. That we're able to bring down.

Is it a partnership with Zillow to do a better zestimate or truly augmentation copilot for the existing true appraisal reports that are used for the underwriting.

For the true appraisal reports that are used in underwriting. Got it. Because the issue with Zillow and every will kind of tell you this, this is like super inaccurate. Like, you know, like people are like, oh, like, yeah.

It's mostly based on like recent sales in the area. It's not actually the quality of the building.

Exactly.

Right.

So what we're able to do is.

Even take into account remodels.

Exactly.

Because they don't know.

Right. They don't know. They don't have the data. And what we're able to do is have this digital twin like literally of a property. So it's actually along the way as we're, you know, we're building this and selling, you know, software appraisal sort. We also have the most valuable or property data set that anybody's going to kind of have to. Super accurate. What were you guys doing before this?

Sure.

Before this we were students at Carnegie Mellon University. We dropped out. There we go. Yeah, yeah, I'm sorry. There's a. A couple guys dropped out of high.

School, so it's not really special anymore. But they are formed here. Talk to us about traction. How are things. Things going?

This has been going super well. We started selling 20 days ago and we're at $124,000 in.

Congratulations. You were correct to bust the confetti.

You guys get. Do you guys get the round down already? We are. We are still filling out a round. Late stage talks with some, with some leads.

Good luck.

But it's looking like we're gonna.

We're.

Congratulations.

Pleasure you.

When did you first discover yc?

Oh yeah, that's a good question.

Discover YC So My freshman year roommate from Carnegie mellon was actually ycf24.

Oh, there you go. Told you about it.

In my mind since then, I was like, okay, I have to do this. Okay, you got it. And then, you know, we did it. So welcome.

You're in league.

You're in the league now. You're in the league.

Welcome to the league. Welcome to Silicon Valley, and welcome to demo day. Thank you for stopping by. We will talk to you guys.

Good to meet you.

Let's bring in the next crew. Thank you so much.

We got a line.

We got a line out the door. We're going to bang through these. We got.

These guys got QR codes on their sleeves.

Bloom. Yes, Bloom. Are you building Bloom filters?

No. No.

What are you?

Easiest way to blooming onions. Nope.

No.

Okay, break it down. So lovable. But for native mobile apps.

Okay, cool, Interesting.

We'd love to just, like, show you.

Please, please.

Okay. So have you guys tried to build mobile apps?

Never seen that interaction action before. He's got UI from the future.

So have you guys ever tried to build.

Yes. I wrote Objective C. It was terrible. I wrote Xcode.

It was awful.

Sucks. We love Apple, but, you know, we're very excited about the anthropic partnership.

Yeah. So typically, you'll have to write code. You'll have to build the app in Xcode or something. You'll have to review. You have to get your users to download it and test light, enter an invite code.

Okay.

So with us, I can literally, literally just like talking to my phone, build a native app, and then I can send it to you via literally bumping phones. Do you have an iPhone?

Yeah, I do.

I do.

Wow.

Just load the app right onto the home screen.

Okay. Malware installed. All personal information extracted.

I don't know.

We got half. I mean, this is just using Air Drop, I think. Do you need turn on again?

No.

Oh, no. Live demos.

Yeah, Airdrop. Like, maybe we need another. Are you on the same WI fi?

You want to try?

Yeah, I'll try.

Let's see. Airdrop. Airdrop is on. Oh, contacts only.

Yeah, now it's on everyone.

Okay, I got it.

Okay, cool.

Let's try it now. There we go.

All right.

Skill issue, baby. Okay.

Oh, Jesus.

Is it going?

This is.

I got the wave. You saw the wave, right?

Yeah, yeah, yeah.

I only have RAM public ad, Quick 8 Sleep Wander and installed right now.

Let's give it one more shot you can take. Otherwise we'll have to retry on your phone.

Yeah, it's okay. It's not like this is live or anything.

Okay, you try, you try anyways. Keep. Keep. Yeah, so try. So when someone like tries to build an app with Bloom, right, It's doing.

The weight, but it's not doing the Internet.

Internet just sucks, I think, the Internet. Anyway, so what you would see is you'd be able to open this app on your phones like instantly. Right. And it uses app clips under the hood.

Oh yeah. Okay, so that's how you're getting the app on without me actually installing.

Exactly, exactly.

And then really hacking that. That's awesome. Okay, exactly.

And so the other thing is like when you prom to build an app with us, we also automatically deploy a backend for you that real time syncs.

Data between devices, as I understand app clips. It's like, it's like there's, there's like one app, like the Uber app exists and then there's an app clip that ties to. To Uber. Are you creating like custom app clips? It's all, it's all around one iOS.

Oh, wow. It's one Bloom app clip.

So it's like an app store within an app store.

Yeah, kind of thing. We've talked on the, on our show before about this idea of like ephemeral apps.

Like memes.

Exactly. Like there's a lot of things that should exist, but only like a day.

Yeah, exactly. We've had so many ideas for like funny apps, but we don't want to actually go pay.

There's so many people, people have an idea for an app and you're like, well, you realize it'll cost like a million dollars to build that. Exactly. Like with us, we built an app for, for demo day in five minutes that everyone in the audience could just scan to like vote on our valuation in five years. And it like had a graph that updated in real time for everyone because it has a backend connected to it. And so what we want to enable is a creator economy, but for software.

Okay, under the hood, what are the best co generation LLMs that you're using? What do you like, what's exciting and how's that market developing?

Yeah, so I mean right now we're obviously for the smartest models, we're using Claude for Sonnet Cloud 4, but we're also experimenting with, you know, a smart mode, smart mode and a fast mode. Because sometimes people just want to make like a quick edit to their app. And like literally you can just speak into our phones, right? You just go into like this like edit mode and then you can just type, hey, add this feature or whatever. And so sometimes you just want those changes fast. And what's cool is like if you had this app open, it would also hot reload on your device.

Yeah, yeah, yeah.

Right.

So very, very cool.

What, what use cases are you most excited about? What are you seeing? What categories? Broadly. Yeah, I mean so right now we're seeing people that already think a software as a creative outlet use this. So developers, designers and entrepreneurs.

Sure.

So especially for designers and non technical entrepreneurs, it's great because they can just like be. Their creativity gets unlocked with this. And so we're seeing people build all kinds of things like personal apps, but also apps that I wouldn't have imagined before, like someone in Africa building like a wildlife tracking app for their conservation and then people building like funny apps.

For the most delicious animals to go after to conserve the animals for, for my own hunting for my next hunting expedition.

But, but yeah, what I'm really excited about is like the apps that I can't even imagine. Right. It's kind of like when the YouTube founders put out YouTube.

I'm sure they weren't imagining vlogging exactly. Just like you know, you put out images in chat GPT. They didn't really imagine studio exactly happen.

And for us, I mean it's software so you literally do anything.

Congratulations.

Thank you so much. How, how's your round going? Oh, round is closed. Let's go.

All right, pleas.

Good stuff.

We'll bring in the next team. Welcome to the D stream.

I'm breathing in the microplastics.

Oh yeah. Really? This is violating everything I know about you. Put your life on the line.

How's it going? Hey, what's happening?

Hi, nice to meet you, I'm John. Pleasure give away. I don't have long. Yeah, no worries, no worries. Can you introduce yourselves? What are you building?

Sure. So we're Morpho AI. We're building a software tool for engineers that are building new robots and new machines.

Oh, interesting.

Yeah. So I came came from the manufacturing tech world. We both met at Harvard. I was an mba, he was a postdoc. And you know, you should talk about yourself too. Yeah, absolutely.

And yeah, I met her when I was at Harvard. Like she said, we got an introduction from a mutual mentor. I did my PhD at MIT, focused on automating the design of robots. So it seemed like, you know, wanted to bring that into some sort of product, show people in the world how useful it was and how it could change the way people design. And she was super excited about changing all the Pain points in manufacturing. So we're doing this. What is exciting in terms of robotics in manufacturing? There's a lot of noise about humanoids, but we talked to a lot of.

People who are just robotics and manufacturing, or is it a tool to accelerate the manufacturing of robots? Second one.

But the main output, beachhead market is really in industrial robots. Okay, yeah, yeah, okay. So we are both examples of what those look like. So the crazy stat that we found.

Is, you know, if you're actually buying a robot off the shelf, you can't actually just like put it in the factory floor. Like 90 plus percent go through a customization process. So that's like six months of lead time. And you know, it takes up a lot of engineering hours. So one of our customers, they were trying to build a full new industrial robot arm. Six months gone in, you know, arms not lifting. They came to us and in two days we basically redid their entire hardware design.

Interesting.

So quite literally we're allowing engineers to build new robots overnight is the hope, and in the future in a matter of minutes.

How concentrated is the robotic arm market? Are there just a few companies that you really need to integrate with deeply or do you need to create something more generalizable out of the gate?

So we're starting out with a little bit more of the OEM side of things, but also these integrators that are buying these arms and saying I now need a new hand. So out of like the one 50,000 robots that get deployed in a given year, most of them have a new hand that's made. And so now you have a generalist engineer trying to make a new hand for four to six weeks in a new design. So really plugging in in that early stage of what do I build before we even get to the programming part?

Yeah, the whole idea is you just have to input the task specifications that you need it to solve and then as much as possible, we're automating of the mechanical and somewhat the control design side of things. Is there a lot of data that you need to feed in? Is there a lot of data that you need to pull from the manufacturer before you can.

We work with parts that manufacturers have.

And that they like to work with. And aside from that, it's test specifications. But we, unlike a lot of the gen companies out there, we do employ some gen solutions but they're all trained from simulation and not from data set. And that's really important because the data.

For how do you go from design.

To some how well it's going to Work that. That doesn't really exist. Nobody takes logs and.

And curates data sets of things they.

Built and how well they worked. Sure, sure, sure.

Talk about traction. Sounds like you guys already are in market. Yeah. So we actually just got a grant from the UK government. Two and a half million British pounds last couple of months. Non dilutive. Fully non dilutive. Congratulations.

We love it for that. Jordy. Oh my God, my ears.

That's loud in here than out there. We've got, I mean Europe just shooting themselves in the foot. People are going to be like why didn't we.

Why didn't we get at least like a quarter point or something? Anyway, congratulations. Thank you.

None of us are British, but they basically.

We're setting up an office in London. Like we're really excited about. About working with them and setting up a. Of course there's benefits.

We have a lot of collaborators there as well.

It's fantastic.

That's an amazing outcome for that last thing. Bull bear on humanoids.

Yes, humanoids. What's your take? I'm bare but like medium bear.

I don't know.

It was like.

Okay. If you're gonna build a humanoid.

Which humanoid? Like people come in all sorts of sizes and shapes. A construction worker is not the same as like a toddler or something like that, but like ballerina.

Exactly.

Linebacker looks different than. So you're gonna need custom designs regardless of what you do. But I mean the other side of things is just like what is the application right now of the humanoids that isn't solved better by re engineering the things around the humanoid? And that's, that's, there's a. There's a long tail there. So we hope we can help people to design the humanoids of the future. Yeah. Just don't think it's here yet. Yeah, yeah, yeah, yeah.

I think there's.

Yeah. You're not saying embarrassing 100 year timeline or even maybe a 10 year time.

I just think it's a little.

I completely agree. Very reasonable stance.

Awesome.

Anyway, congrats to meet you guys. Congratulations. Thank you. I'm gonna give you a slow progress so we don't have to deal with the whole. Or we can do. Okay, perfect. Anyway, let's bring in the next team.

We're putting the word out.

Thank you so much. The table is now covered with confetti.

We predicted millions of dollars for free.

Head over across the pond. This is the greatest capital extraction event, the greatest wealth creation event in history.

In history.

Since the Boston Tea Party. Anyway, good to meet you.

What's up.

Welcome to the stream. My name is John. How are you doing? Can you introduce yourself in the company?

Yeah, absolutely. Yeah. So I'm Rajith.

We're Prism. Okay.

Prism is an agentic observability company.

Okay.

So we let developers configure agents to watch their production systems.

Okay.

So read logs for them, watch videos of their customers using software and then enable them to take certain actions. So like create issues on linear GitHub.

Linear sponsor the stream. Let's go.

I did that on purpose. Service and send reports to Slack.

So that's great. That's great. Well, how's adoption been? How are you selling in? Are you going medium sized? Scale ups other startups, YC companies, enterprise? What are you thinking?

Bottom up. So this is a tool that every developer needs and every developer can use. So we're starting with the YC community.

Cool. We're completely self serve.

So there's 23 people on the platform and counting.

Yeah.

More people sign up and start using it every time. Were you guys iterating through the batch? Oh yeah, yeah we were. So the first version of the product.

Yeah.

So it's like we watch videos of people using software, right?

Sure.

So the first version of the product was these two watching everyone's videos and just giving them issues and like sending them Slack messages and stuff like guys, this is broken, you need to fix this.

Yeah, yeah.

So that we were basically like a services business but we didn't tell everyone, we told them it was AI. So that was the first version of the business. Gotta start somewhere. That's awesome.

Yeah.

What, how's, how's fundraising going? You guys in the midst of it?

It's going great.

We're in the midst of it still, you know, still trying to finish up the round.

Yeah. Good luck.

But yeah, we're excited. Excited.

That's fantastic.

Awesome.

What were you doing before?

I was at Greow, which is a COD review company, I think you guys.

That's amazing. That's a great website.

You too. I was a software engineer at Palantir.

Oh cool.

And I worked in product at Johnson and Johnson.

Oh, very cool.

Alex. Alex. Big pharma.

Yeah, yeah, yeah.

So Land and I met in high.

School and then all three of us.

Were at Georgia Tech together.

Oh cool.

Alex actually had a post on LinkedIn this morning about how he left 850k a year behind at Palantir to come work with us. So there we go.

Well, I think you'll make it all back. Just burn the boats. Anyway, good luck with the rest of demo. Appreciate it. We are ready for the next guest on the YC Demo Day stream.

10 minutes left.

10 minutes left and then we gotta go. Yeah, yeah. We can speed through this as much as we can. We got 10 minutes until we gotta go to the airport. Is that right? Or surviving. We got 10 minutes more. Come on in. Don't even bother introducing yourself. Just tell us what you do. What company are you building?

How are you doing our clarm? We are perplexity on internal documents. Okay. Search is being heavily disrupted by AI at the moment. As you know, Google is being disrupted by perplexity and we're doing that for internal enterprise search.

Okay. Competition with Glean. They just raised a bunch of money. How are you thinking about replace them? You're going to replace them? They're just getting started and you replace.

Replacing Google? We're replacing Glean.

Okay. Okay. So how do you do it? What's different? How do you actually integrate? Are you building a bunch of integrations? Are you building on top of an integrator?

We are. We have our own integration. We found that. That the. The only way to do this, to actually build AI agentic search, is to build it from the ground up.

Yep.

And that's why all these legacy players have to do that as well.

What's more important in integration with Google Docs, for example, or integration with like the data lake? That's maybe that maybe somebody has a snowflake installation.

What's more important? It's important to have both of them.

Both so that you can connect both.

And you can actually have about 45 connections.

45 connections. Okay. How about customers? How many of those got?

We have eight. We only launched two weeks ago.

Congratulations. Congratulations.

What's the biggest challenge? Is permissioning hard? Maybe at smaller companies it's not as much of an issue, but as you go kind of upmarket dealing with all the different types of data. And this is why B2C companies don't play in enterprise space. Because when you have to look at Salesforce data alongside messy Excel sheets, then it becomes harder to connect them together. But that's the value in it.

Where can companies go to get started?

They can go to klom.com they can try our live demo now.

Congratulations.

On demo day they can talk to us directly.

Fantastic JLC reversal.

Thank you very much.

It's a fantastic.

Guys, congratulations.

Let's bring in the next team. We're doing lightning round. Lightning round. Lightning round. Lightning round at Y YC Demo Day 2025 welcome to the stream. What do you do. What are you building?

AI co pilot for Solopreneurs. Okay, get out of here.

How's it going? How many customers do you have? What, what data are you sharing today at ycw?

Who's more cracked? He's definitely the most cracked engineer we have, we have ever seen. So we have gone from 0 to 300k ARR in this last nine weeks.

Congratulations.

Yes. So that's what we're doing. And yeah, we're seeing this future where solopreneurs are going to completely wipe code and run their entire business on cactus.

Right.

So that's what we're building. Great name, great name. Thank you. What were you guys doing before this? We built a previous YC company. He was a founding engineer. We scaled it up to 2.5. He's a crack sales guy and the cracked engineer and together we are the crack founders.

So crack sales guy, how are you actually selling? This thing is a hand to hand combat with these solopreneurs. Or are you doing like viral marketing? We've seen levels get a lot of attention for solopreneur stuff. How are you actually attracting people?

Absolutely.

So it's mainly through word of mouth that's been spreading.

What we also do is outbound, where we call them.

So think about a caterer, a private.

Chef, they're busy cooking all day long. Call them. They don't pick up as expected.

They're busy.

We leave them a message saying, hey, you just missed an opportunity, guys.

So yeah, they get back and then they set up cactus.

They get incremental 10 to 15k in a month revenue. And the biggest thing is the headache.

For them is gone. Right. They don't have to answer the phone. Yep, that's the best. That's amazing. 300k. ARR. How's the fundraise going?

It's going great. We just got completely oversubscribed.

Well, congratulations.

Thank you.

Thanks for coming on the stream. We're bringing in the next game. Have a great rest of your demo day. Come on down. We're live from YC Demo Day 2025 and we have our next team in the building. Hello, nice to meet you, I'm John. Welcome.

Good to meet you guys.

Would you mind introducing your company? What are you building?

Yeah, for sure. So we are building lamari which is essentially helping go to market teams build tools internally instead of having to buy super expensive SaaS.

What, what tools do go to market teams need like golf clubs. Go club buying machine on subscription and steak dinner booking.

That'll be nice. I wish we did that. But we are helping them like from anything from deal scoring, qualifying leads, making contracts like anything down like the sales pipeline.

Got it, got it. Okay.

Yeah. What is the future of the stack look like? Are you guys gonna basically. Are you trying to verticalize effectively and allow people to build custom software at every point? Yeah, I really think we're going to look back to this era of SaaS of like having all these generic tools that you're using and think that was really silly because why wouldn't you have software that's custom built for your company, for your process? And so I think exactly that we're going to start with replacing some of these really point solution software. But I think in the future every company's going to have their own CRM. What were you guys doing before this? What were we doing before? I was at Stripe, Sam was at Google.

Amazing.

Yeah, we were sort of a non traditional background.

Yeah, yeah, exactly. Who's the key person actually using the tools? This for a non technical person?

It's a non technical person within these go to market teams often like a revenue operation, sales operations.

That makes a ton of sense. Awesome.

How's traction? It's been great. We're at 90K ARR in.

Congratulations.

Obviously we're out of confetti.

Yes.

Yeah, we are. We're. We're pretty much out. We got, we got a couple left. Okay. Okay. I'll let you. They're kind of busted anyway.

Thanks so much for coming on the show.

Thank you so much.

Guys, let's bring in the next team. We have five more minutes, right? Something like that. Let's go. Five more minutes.

Losing his voice.

Let's go. I'm losing my voice. Welcome. Welcome to the stream. Introduce yourselves, introduce the company. Good to meet you.

All over your shirts.

I'm Yoav and this is Shia.

We're second time exited.

YC founders, second startup.

Thank you.

Addicted to startups.

Addicted to startups. We're building third chair agents for in house legal teams and we're starting with.

Media and entertainment companies. Oh, interesting. Very niche down. Not just like legal AI, but you've actually found a.

You want to dominate a small market.

No, it's a massive market.

But we're starting by dominating media and entertainment.

Yes, yes.

We're starting by helping. Helping media and entertainment companies find IP infringements.

Oh, interesting. And we collect evidence around it and then that's revenue driving immediately. Right, Exactly.

It's a revenue generating workflow.

Is that the, is that the business model? You take a cut of whatever you get or is it more seat based?

We have a software model but we also take a cut of what we get.

So it's kind of amazing for the Apple.

I like that.

We're exploring a little bit how's traction full stack.

You're finding the IP infringements and then you're actually sending letter demand letters. Someday we're going to be a vertical AI law firm and yeah, there's a lot of. We're handling the entire workflow right now and a lot of it is being done through agents. But our customers just think of us as people who get things done and they don't care about how the other like the black box is working.

That makes sense. Yeah. What metrics have you been sharing? How's demo day going? Does that mean is this your third demo day then?

It is second demo day.

Second demo day. What's that?

Were you co founders together last time?

No, we had separate startups joining forces.

Social media analytics. Now we're in legal. So YC alumni network is strong.

You know we teamed up and yeah, traction's going great. Cool.

We just crossed a hundred thousand ARR.

We're working with. Congratulations.

We're the biggest media entertainment companies in the world now. Expanding to brands, doing stuff like marketing compliance.

So yeah, that's great. Well, congratulations.

Thank you guys so much.

Stream. We will talk to you soon. Let's bring in the next team. How are you doing, Q?

I like this qfx.

Introduce yourself. How you doing? I think solo founder. We got to give him a hat. A TVPN hat.

Oh yeah, definitely.

Introduce yourself. Introduce swap here.

Perfect. Let's swap. Yeah. So hi guys. I'm Anan. I'm CEO of QFX.

Cool.

We're making a 24 7. It's 24247 Stock Exchange.

Okay.

So we're going to let institutions and retail trade traditional assets like US equities and commodities real time 247 without brokers with loads of leverage just like you.

How's the traction? But it feels like it's really hard.

To get this thing underlying. Is this a sneaky blockchain company? There's no blockchain. No chain. There's no blockchain. It's completely off chain.

Okay.

It's basically. It's like, it's like a crypto exchange but without the blockchain parts. We've taken those improvements and moved them over to the traditional assets world.

Okay.

And attraction is good. We've been running it. Well, we've not been running it to the YC batch because we're not licensed yet.

Sure.

But we've been running some internal experiments. Yeah, some internal experiments. The current YC batch. And due to those experiments, we're launching in a couple of months with the light license. And offshore. Offshore? Offshore in Bermuda.

We'll get you.

Bermuda. Nice place. You guys have a. Yeah, a lot of trips there. Yeah, exactly. Free rum if you come visit our office. There you go.

Fantastic.

There you go. How do you get into this? Yeah, I was a quant. Yeah. Tower research before.

Okay.

And my co founder was at Citadel. Well, you're our client now. Yeah, exactly.

Well, congratulations.

Congratulations.

Yeah.

Great to meet you guys. Cheers.

We'll talk to you soon. Thanks. Come on.

Loads of leverage.

Loads of leverage. We love to see it. Welcome to the stream. Tell us what you're building.

Wait, were you here last? You were here last time, were you not? No, no, no, no.

Okay.

No, sorry, sorry. I thought I recognized another.

Yeah. Anyway, introduce yourself. What do you. What are you building?

Yeah, I'm building in AI accounting for small businesses.

Oh, okay. Cool. How's it going? Do you have a small businesses on the platform already?

Yeah, yeah, we have a few small businesses. We're just trying to automate all of their bookkeeping so, you know, chase people down for receipts. Yeah, make calls.

I feel like there's so much that's already built into the accounting suites. Like do you have to sit on top of QuickBooks or do you actually pitch people, hey, let's rip out what, your existing accounting solution.

No, we're sitting on top of QuickBooks. There's no point replacing the software. Yeah, we're just repeating. Replacing the service side of things. Consolidating all the scattered data. That makes sense, you know, sits in all different kinds of places. Your WhatsApp, your email, your stripe. Sure, everything. How were you doing before this? Sorry? What were you doing before yc? I was building a health tech business. We're selling AI patient triage software to clinics. Awesome.

Cool. How's traction been? How's the raise going? How's demo day been?

Yeah, demo day been great. We are raising $2 million and roughly like 3/4 finished. So just trying to wrap it up.

Congratulations.

Classic. Two on 20. That's funny.

Love it. Well, congratulations. Hope you have a great rest of your demo day. Last one, Bringing it in.

Closing it out strong with what's going on.

Sim Studio.

Studio.

Are you simulating things?

Yes, we are simulating. Hey, how are you? Nice to meet you.

Okay. How you doing? Great, I'm doing great.

How are you?

I'm great. Break it down for us. What are you building?

It's an open source platform to build AI agents.

Okay.

Yeah. So it's developer focused. It's like a figma, like canvas to build agents.

Interesting. How many GitHub stars you got? We gotta ask.

50 to 4,000 in the last two months. Wow.

Wait, wait, you were at 50 and now you have 4,000?

Yes. Wow.

Congratulations.

Thank you. I appreciate that. Thanks. Yeah.

4,000 GitHub stars. You love to see it.

Yeah. Congratulations.

We got two more.

I can't believe Gary let us bring these in.

Oh, yeah, he let us.

The cleanup after is going to be interesting anyway.

How's traction been in on the sales side? I imagine you have a product that you actually sell on top of it. Not a nonprofit.

Yeah, yeah. So yeah, we can't disclose revenue numbers, but we have a lot of great customers.

Cool.

So, yeah, Department of DefenseCore EPIC Global. A bunch of huge, huge, huge. So the round's definitely done? Definitely done.

Round's done.

Okay. Yeah. What were you doing before this? So I was at Berkeley and my co found Berkeley.

Let's go. Let's hear from Berkeley, baby. Right across, right across the bay.

Go right across the bay.

We love it. We love Berkeley. Yeah, I'm completely covered.

It's everywhere.

Congratulations, I appreciate it.

Yeah, thank you. Yeah, that's great. What's next for you guys? Next is just making our customers happy. The Department of Defense, where do you even go from there? Yeah, I mean, just making developers happy, like building the product out more and more, you know, and I think, you know, developers love us and big customers love us, so we're just like keeping that energy going, keep launching new products, building the team. We have a really great, like killer engineering team from friends at Berkeley. So yeah, we're excited to keep growing and keep building.

What's the, what's the key value prop for, for. For building platform for AI agents? Is it like interoperability between different models? Is it the ability to scale? Is it just price and cost?

I think the question I have is like even last YC batch there was a bunch, there was companies with this pitch. And I think the challenge is everybody wants to build infrastructure and, and travels for agents, but then it feels like you can build good software, but it's maybe even harder to get the kind of companies that can build high quality agents that actually have value. What's, what's the secret to like finding even customers that are not just going to sign up but actually get value out of the product. Yeah, that's definitely true. I think a lot of people, especially right now, it's very in vogue to adopt AI and so there's a lot of like top down push from companies to adopt these AI implementations. But I think the biggest thing for us is that we're focused on not creating easy abstractions to make it easy to use. And I think that's where a lot of people fell short. It's like you're creating these abstractions that make your platform easy to use, but it's actually not powerful enough to really put AI into your production system. And so for us we're really focused on actually might be a little more like might be harder to use. But because we remove the abstractions, you can actually power relatively complex applications like real world simulations, deep research, data transformations. Because a lot of companies are sort of going after the sales and marketing, you know, use case and for us are more focused on the developers and actually production systems.

Interesting. Awesome. How much is real world simulation like scaling right now? We've talked to some of these companies and it seems like it's almost like video generation. It feels like very nascent. We really haven't had like this breakout Studio Ghibli moment for real world simulation. Like how is adoption going there?

Yeah, it's actually going quite well, I think.

Yeah. What are the applications?

Yeah, so the applications of that are essentially simulating like, I guess like one that would be interesting would be like international affairs. So like understanding how like global events are going to play out. Using agents. Yeah, so that's like a broad topic, that network.

Yeah, yeah, I've heard about that. With like economic modeling.

Exactly.

And like housing prices, you can actually have agents running. And he was always like just like Grand Theft Auto level.

Right, right.

But now it's like, oh, what if each of them has like an internal reasoning engine powered by an LLM and that's like 130 IQ instead of like turn left, I'm running a star.

Right.

It's much better.

Yeah. And I think the thing that really our, our platform unlocked was being able to run thousands of agents in parallel at the same time. And I think that was one of our grounding thesis was that you know, we wanted to create this environment like SIM Studio comes from building simulations of things. So launching, you know, 10,000 agents at a time and perhaps some of them are going to come back and give you an accurate result or some of them, you know, might inform you in an interesting way. And so you take those aggregated results and you go do something with it.

Very cool.

Yeah.

Thank you so much.

Yeah. It was a pleasure. Thank you for having me. Yeah. Yeah. Great meeting you both.

Fantastic. And that is the end of the our demo day stream. We will be back in Los Angeles tomorrow, live from European. Yeah. Thank you to White Combinator team. Fantastic.

Major white pill.

San Francisco's back. Gary Tan's back.

He.

He never left YC Never left.

But Rosewood is back.

It's. It's just a fantastic time in San Francisco. Fantastic time to be here at YC Demo day. Thank you for watching. We will see you tomorrow. Goodbye.