The Quest for 1st Cheque-Episode 6- Founders of Doppio Labs

Um, first of all, thank you so much for taking the time out for this, Pierre and Swam, really appreciate you guys. Um, I'm Natalie, and I think the first time I heard about DocuLabs, which is your startup by the way, is when Pierre connected with me on LinkedIn and sent me the website of DocuLabs, and I checked it out and I thought it was pretty cool. I mean, I'm not gonna go ahead and explain what it is because I think you guys can do a pretty good job at doing that. But anyways, why don't you start by, um, you know, introducing yourself, who you are, and what inspired you to work on Topia Labs.

I'm a student at NYU studying computer science and economics, but I've been doing software engineering and development for around— since I was 7, so around 13 years now. And it's taken various forms from worked in some startups, some big tech companies, but really what I found is you can make the most impact in a startup, so that's why I'm here.

Um, so I'm from Europe. I lived in Paris and London, and I arrived in the US this year actually to study finance and computing at NYU in the business school. And this year we had to go through the— well, at least we didn't have to, but most of my peers and I decided to go for the investment banking recruiting process for everything like the bulge brackets, like Goldman Sachs, the boutiques like Evercore. And that meant dedicating a lot of time, probably around 15 hours per week, more for some honestly, to networking with people on LinkedIn through alumni connections, anything we could find. And that was an extremely tedious, repetitive task. And I talked to Sam because he also recruited for IB a little bit, and we just decided that we definitely could do something about it. Honestly, it's more of a passion, like personal project than anything else, because it's definitely a tool that we could use and hundreds of students that we've talked to about this issue and about the solution would definitely love to see become a reality.

When you first told me about this on the call, I was like, okay, wait a minute, I've experienced this before. I know what this is like. I know that the networking process and not just that, but just like especially when you look looking for something, it can be so much more tedious, time-consuming, and just, you know, so much more pressurizing because you have to be a certain someone. So what exactly is Dopio Labs?

I can get into what is Dopio Labs, I think, question pretty well. So our goal fundamentally is to be the go-to people search platform. Sorry. Um, what we've realized is that not just for people going into recruiting, but honestly everyone, kind of has this issue with the way modern recruiting and modern networking is for professionals. And our goal is to revolutionize that by providing a system where all you have to do is say who you're looking for, and we'll give you exactly the best people for you to connect with. It's all personalized to you as an individual. I hope that will help not just people recruiting, but also people from all types of backgrounds, whether it's marketing professionals, students, people trying to switch careers. That's our goal.

So how can you walk me through the whole process of, you know, starting from creating a profile to like actually being connected with someone?

The way it works is you upload— we're right now starting with recruiting, so you upload a resume and we'd scan your resume, we understand what you're interested in, and then we'd go through our database and we'd scan people and match them with people who have the similar interests, similar backgrounds. This goes beyond just school matching. It goes into high schools, hobbies, clubs, fraternities, things that you wouldn't necessarily have an immediate search engine for, which means that people who might not necessarily have the strong alumni network also have the opportunity to connect with people.

At our school, it was very easy to connect with alumni, like especially for banking since like all of the school goes into that, a very good feeder. But what we're trying to do is feed the rest of the population that doesn't have that strong alumni connection and there's nothing currently to, uh, to help them. So it's really about finding a solution for that 99% of people, democratizing really finding connections easily that really do matter.

Let me start by actually making sense of what exactly is happening. So you start off by uploading your resume and like, so how do you connect with people? Um, from, you know, do you, do you say where, like, what industry you want to get into, what sort of jobs you're looking for before you introduce to people of that specific network? Or like, how does that really work?

Started off structuring it as a per-company search, but now moving more and more into like an LLM query. So you just type in what you're looking for and then it goes to our proprietary database system and then searches through that.

Okay. And, and it's— does it scan your LinkedIn, social media?

So You— so the way it sources for other people is it scans their LinkedIn and we're uploading— we've provided a space for you to upload your LinkedIn as well as your resume together. And we're planning to add social media integration later. It's not something we've fully built out yet, but it's something we've been talking about.

And then it tells you more about, you know, the common connections and also tells you more about the interests that you guys have so that you can connect On a personalized level, just beyond networking. Okay. Okay. Okay.

And so I'll share a demo if it helps.

Yeah, that would be amazing.

I would love that. The way it would work, so you'd be initially prompted with a search bar. You would write whatever the, whatever you want, something precise and tangible that you can't currently find on LinkedIn. So LinkedIn right now, we can just search for a company and people by people, look them up, which is extremely tedious. So with us, you'd write what, who you want to find, um, like software engineer who plays golf and is from your school, your high school, wherever it may be. That's one way it could work. The other way is if you just want to look through an entire company, that's for more for job recruiting. So you would select a certain company and we would then match you with people from that. We would analyze, like deploy agents, AI agents who would scour through the entire company and that would give you back a list of people who based on your resume, based on your Instagram match who you are as a person. So you can connect more on a, I don't know if it's emotional level, but something a bit more deeper than just we both like finance and high frequencies.

Similar interests.

Exactly. And then to make it as automated as possible, you can have the LinkedIn if you want for now, uh, that will be removed later. And we just write you a tailored message that has the highest chances of getting a response. And from that, it's, well, it's your turn to ace the interview pretty much.

I see. I mean, that, that was really helpful, the demo, just, you know, in terms of I mean, it's easier to see how it works and understand, you know, how exactly did someone navigate through this platform. And I think this is the platform which I and so many out there wish they had, because, you know, if you go on LinkedIn and you look up, you know, something like this, it'll give you all these different profiles, and that'll only leave you feeling overwhelmed. But at the same time, you won't have any connecting points. And I think that this is something which somebody who spoke to like a few months back also said that, you know, he was looking for an internship and the way he would find it was finding Scottish people who work at, you know, the company he was looking for. And I think doing something, you know, having a platform of this sort is definitely very helpful. But I'm curious to know, you know, how do you guys go from that idea stage to being where you're at right now? And where are you currently in your product, you know, in your startup phase?

We started around February with the initial idea. We're hoping to get into the YC X25 batch, but we had around 2 weeks to get the entire thing built and we're like, let's give it a shot. So it was a pretty hectic 2 weeks. I think I pulled 2 all-nighters back to back, which was fun. We got, I think, a lot of our scraping and initial matching algorithms built out then. What we really struggled with was data. So as you know, LinkedIn is probably very secure with their data. They don't like it when you try and scrape their data. So we realized is that, okay, scraping company by company is probably our best idea to get started, but it's not scalable enough to give us what we really want, which is a widespread data, universal database. So we stepped back a bit. We redesigned our matching algorithms to be more robust. Instead of not just using text matching, we're using an advanced RAG system. And then we also went and built out an entire network of scrapers. That's what we're still working on. It's been a pretty difficult challenge to figure this out, but it should give us a lot more control over the data we have, and it should give us more flexibility and scalability.

This is— so you guys built this all in like 2 weeks?

We built our first prototype, our first MVP, which scraped off of a subset of the Goldman Sachs database in 2 weeks. And since then, we've been focused on getting more data and improving our matching algorithms.

A few months to understand how to get all the data on an extremely large scale. So now we're able to scrape hundreds of millions of profiles, and that took us 4 months of technical issues.

Yeah, because if we tried scraping LinkedIn, they put up wall after wall to make this impossible. So it's just a constant, like essentially a game of whack-a-mole, but it's pretty fun.

What are the integrations that you guys support on your platform again?

It's LinkedIn primarily right now, though our future goals are more social media platforms. Specifically, Instagram is next.

Curious to know, so like, what's like, what's the inspiration behind the name? Nickname, but I don't really know what's like, um, inspiration behind it. Curious to know.

Pierre, if you want to explain what coffee chats are, it's probably a good place to start with the name.

I had to do, I don't know, 60, 70, I don't really know, like tens of tens, dozens upon dozens of meetups where I go somewhere around New York City and I have coffee or a pastry, whatever it's going to be, with someone who works at a firm in a bank. And the industry terms is coffee chat. It's the same in banking, quant, consulting, tech. And it's the main way to really bridge that job application portal. So you've got hundreds of Goldman Sachs, probably 320,000 applicants for very few internship positions. And the way you get in those positions is by talking to someone who's within the company. And that's what we also wanna breach is that we've, like, you've got now those automation tools for job applying, which create just massive, like you apply to 10,000 internships for very few results. And what we want to do is make it all about, um, qualitative results instead of a quantitative one. And our reason is that this has nothing to do with the name Dopio. Basically, it's just coffee chatting. Uh, you've got to talk to someone in the company to get your foot in. And Dopio is a pun on, uh, well, it's not a pun, it's a double shot of espresso in Italian because it's two people meeting and talking for the first time.

Wow. I didn't realize that. I mean, I didn't know it had to do anything with coffee, to be honest, because the name doppio— I mean, I don't know Italian, but then doppio and coffee did not correlate. But then now it makes sense why you said that.

Yeah, it's a bit of a bit of a trauma, which is why I felt like explaining it.

Okay, I'm glad you took it up. But anyways, I was wondering, like, you know, so now that you guys, you know, started to work on this, do you guys have any users on your platform? Or, you know, how, like, where are you currently at in your startup journey?

So right now we're at the point where we've built out a lot of this tooling, but we're still kind of figuring out. So getting all these data is Getting all these users on our database is gonna take some time. You know, we can't just hit download and download 160 million profiles from LinkedIn. So it's gonna take some running time to kind of get this database populated. So in the meantime, we're filling up a waitlist of users. We currently have, I think, 320 signups in the last week, and it's continually growing. And that we're doing with clubs. So our goal is that when we have release open, we'll have a flood of users coming in testing our product. And just have live users immediately. And that's our goal right now.

Platform is we're reaching out to university clubs right now. I think we're at, I mean, we started very recently, probably 3 days ago with this, but we've got 7, I think. Yeah, 7 university, well, 7 club, like 7 universities with different clubs in each who are willing to, we're gonna spread our platform so that when fall semester starts, And when really that recruiting season starts, which is when we think, well, when we know that our platform will be fully released to the public, we can launch it in fall and there's gonna be a massive influx with all those clubs spreading the word around and quickly scaling it to all the universities as the word spreads. Facebook, when they released university by university, were doing the same.

Actually, you're very smart. You honestly just get more users and the fact that you guys have more than 200 I mean, I'm one of them obviously on the waitlist, but signed up immediately after you told me about it. But I think that having more than 200 users on your platform is pretty cool just for now because that shows that people are eager, people wanna use it. It's just about when. So when you guys plan on going live?

I think timeline currently is within the next month is to go live, but we're planning to kind of slowly roll it out so it wouldn't be all at once. 'Cause we wanna kind of make sure that our systems are reliable and robust and we wanna figure out kind of what the cost per user is gonna look like too.

What's, what's, what's your business model like?

Start first with the consumer platform, which is what we just showed. That's gonna be starting out like in a month, month and a half, and depending on how fast we're able to code the whole project away. So users are going to be paying, um, there's going to be a very couple trials, uh, so you can test it out the way you want it. And then there's the, of course, a payment plan. Um, right now I said about $20, uh, $20 we're thinking. It's going to be— we discussed and everything. Um, that's the first step for the consumer platform. And there's also, um, a platform that we're making slowly for businesses where that's more so to get leads, reach out to other companies. And the second part is also within companies. An issue we found, because we worked a bunch of internships at very large companies right now. So he's working at Cisco, Cisco, worked at HSBC, right now working for We work for companies that have hundreds of thousands of employees, and an issue we found is that it's very hard to find someone to talk to when you have a specific question, especially in tech, someone who's really mastered a particular topic. And what we're gonna do is that we're going to plug in on like all the data, like profile, all the profiles of human resources people work at the company. Yeah, exactly. Uh, I grade it into our, uh, system. And so now people will be able to use our query system and just type away, find me a person in my company best suited to answer X question, X topic, and we're going to give you the best person for it. So, so the, the aim is really to make work much more efficient for those companies. Another thing we're gonna be able to do with, we're gonna be rolling out to companies is creating teams. So as you said, our platform is to match people together and we're going to be analyzing, you know, their, like we're doing for consumers, Instagram, CV profile, LinkedIn, lots of data sources to see how, which people would best fit together, best work together. To create a very efficient team, a very driven team, and a team that works well together and likes each other, because that would mean, well, the best way to work.

Question is, I mean, there's so many platforms out there that are trying to do exactly what you're doing. And because of AI right now and these low-code apps, there's going to be even more competition than what it is right now. So I was wondering What would you say is your mode of the startup right now? And what is your plan to differentiate yourself from your competition and keep growing?

Two things. First, data. Data is very difficult to get and to have these systems of scrapers that we've written out is difficult. Like it's not something that people can just go and make in a day. It takes a while to figure out exactly what each stopping point is. Unless you're willing to dedicate the time to go down that rabbit hole, you're not going to be able to get to that solution. Second issue is that we have a very intricate matching system. It uses a mixture of LLMs, embedding models, and RAG to do our matching system. And it's not necessarily something people can replicate really quickly. It's going to take a good amount of reading and research to get that to happen. So we know there's people who are trying to make something similar, but the question we wonder is like, is their quality going to be up to par? Are they going to have the data we do? If we don't have those two, they're not going to be able to compete.

We've got one startup who's quite similar to ours. And what we found is that they have a good source of data, but their search algorithm really lacks. Was we've really worked on ours and it's much stronger. And those take quite a bit of time to get any results, which is why we made the search by company, 'cause it means the algorithm only has to search X amount of, through X amount of people instead of the entirety of LinkedIn. So you get, you kind of get results really fast compared to other models and the results we give you are of much higher quality.

As long as you've got data and as long as your algorithm works pretty well in terms of connecting you with someone you're supposed to be connected with, I think that is— and the end result and the feedback you get from users when they see that, hey, you know, I got, you know, I got connected with this person that led me to my internship, or that led me to my first job in XYZ industry. And I think those sort of testimonials, that sort of word of mouth, and that sort of results is what is ultimately going to help you become the best out there because yes, I asked this question to you all and I know for a fact that there's gonna be immense competition out there. And with no-code tools, like I used Lovie Build like when they were free during the weekend and I'm not sure if you know of it, but it's a low-code platform wherein you can, no-code platform wherein you give certain prompt and then it builds out websites and builds out apps for you, right? Obviously it's front end, it's prototype, but then it does a pretty, and if you connect the Supabase, it does pretty good job at giving you exactly what it needs. But then, you know, apps can be built in minutes, but then what you, what differentiates your startup is like one, the drive, the hustle, who you are, and two, the data and the algorithms and obviously the feedback that people get and if it's successful enough. But, so yeah, I mean.

You mentioned feedback in particular, like customer feedback and user feedback is gonna be very important to fine-tuning algorithm especially because As we get ideas of what works for matching, we're able to kind of fine-tune what our matching systems to make that more and more reliable. So yeah, it's gonna be a huge advantage as we scale up too.

Yeah, exactly. We're gonna be using like, if they, if the users find that they can actually connect and there's a high response and hit-off rates, we're gonna use back that data to really improve our algorithm and improve back the matches that we give out.

And of course, like right now you guys have a plan on, you know, this is exactly how we plan on doing it. But then ultimately once you go live, you guys, you know, it obviously depends on what the users say and what sort of feedback they provide you. But then, you know, there's so many founders out there who've pivoted from the original idea and moved on to get better and better because, you know, that is what you do when you're amazing founders and want to build a great product out there. So Honestly, what you're seeing right now could not be relevant for like 2 months down the line. You look at this interview and be like, hey, we said this, but would this really work? Not really. But of course, and it might work. I mean, I haven't tried the app out yet and obviously you guys are still in your early phases and have not put it out there. But then the more the users use it, the more feedback you get, and the more you integrate that feedback into making your product better. Now that is how you differentiate yourself from your competitors out there. Exactly. Great. But I mean, so I was curious, you know, like, are you guys, you know, raising currently, looking to raise, you know, what's the plan?

Currently talking to a couple of investors. There's one that we've got to get back to tomorrow, actually. One is an accelerator called Z Fellows. They're based in San Francisco and they gave us a very nice valuation at $1 billion, which is definitely what we're currently worth. No, no discussion about it. And we're also talking about some investors who are based in Minnesota and invest in really student-led startups, I guess.

So is there, is there a specific amount you guys have in mind about how much you're raising right now?

Our goal right now is to raise, we don't want to raise too much because I think right now we don't have any huge expenses coming up. I think a goal for us right now is keep a small team, build fast. Our main expense right now is scraping. And that's, we brought the cost down from around $50,000 to just over $10,000, which is pretty good cost-wise for the number of users we're getting. And if we can get that figured out, that gives us, I think, a pretty good position. We're not really concerned too much with raising that much money at this point. It's more about building that network and the connections.

If let's say today you raise, you know, like let's say you raise $1 million, okay, or $500K, what would the money go towards? And where exactly would you say you need, you know, to use the money for?

It would start with scraping. That would be $10K right now, could end up being maybe $13K. That would depend between $10,000 and $13,000. The rest of the money, at least for now, would be— so like I said, we really are looking into making qualitative connections. So our money will go into meetup events. What we're going to do is that people who connect on, on the platform, those who really hit it off well, we're going to invite them to dinners, cocktail parties, whatever it may be, so they can really meet not only on, on, on Zoom or phone call or whatever, but in real life in New York City. In San Francisco, all of that. So that would be a big expense, but we think it's necessary to create those meetup places, those interactions to really build up those connections, build the foundation for that. And of course, we're going to also spend a lot of money on software engineers.

Yeah, I think one of our primary things, we also have paid AWS, sorry, we're using Azure right now, but Azure and Whatever LLMs we're using, but we brought down those costs significantly.

You get thousands upon thousands of dollars in Asia credits. So yeah, for now, credit, tens of thousands.

Okay.

Yeah. I mean, I like that you focused one of the main ways to use our money is by hosting more community events because I feel like a lot of in-person events have been gaining traction and I feel like that is what makes experience super unique because, I mean, it's great to meet people online and speak to them, and obviously, you know, coffee chats is great, but then having a lot of people together and, you know, for people to meet each other, learn from each other— because, I mean, I heard it from someone recently that your next recruiter won't be someone who is a 50-year-old at McKinsey, but will be your next, you know, would be your classmate slash your colleague who you were starting with at university. And so, you know, obviously these panels are not just about networking with, you know, the, the people who have been high up there, but also with people who you can benefit from being with.

Yeah, I mean, especially with the ease of development now, I think the importance is less on hiring engineers and more about building the community and the group that's going to end up supporting your app when it goes live. And that's like the primary goal we have.

Quick question. Why, okay, I would y'all be the best people to work on this startup?

I'll take this one. So we both come from a technical background. So I've been working, well, like developing code since he was what, 7 or something? Okay, even way worse than 12. Jesus Christ, man. And I started a bit way later when I was 15 or something. But only for personal. So I never looked for a software engineering internship position, whatever it may be. So there's a technical background there also. We know the space quite well. I mean, we don't have experience working for LinkedIn and all of that, but I mean, like I said, recruiting, we've done quite a bit of it. Coffee chatting, making those connections, networking. I've had I don't know how many hundreds of hours doing it for previous internships, for current ones. So we've got that, we've got the connections, and also, um, we're young and what we want to build is not like right now we're connect through connecting through LinkedIn, but we don't want that in the foreseeable future. We want to end the LinkedIn connection and become the next platform where people meet and form connections, network, all of that. Because right now, I mean, honestly, LinkedIn, it hasn't— I mean, I wasn't alive when LinkedIn was created, but we haven't seen any real changes in the platform and it's not changing with the times and with the new generation. So we want to build the platform for the new generation, the new people who are coming into the workplace, making the deals happen and really be the next go-to for people search, people connections, all of that.

Would the goal be to be acquired by LinkedIn?

Goals to—

I haven't asked them fully yet, to be fair.

But I think our goal is to really fundamentally reshape the way connections work because we don't, I think we don't like the attention economics of LinkedIn. I particularly don't like the idea that everything has to be broadcast to the world to kind of maximize your reach. We want to make things more personal, more authentic, and more direct rather than more, you know, public and attention-seeking, which is I think what we found LinkedIn to be.

Yeah, we, I don't know how many people like students we talked to who have a deep, deep hatred for LinkedIn and since they're gonna be the people using the platform next. I, it's not a great sign, to be fair.

Yeah.

They really hate how we're gonna make connections we find on there. They've lost their meaning with that 500+ connections, which like, I don't have 500+ meaningful connections that are gonna help me shape the world. What we wanna focus on is really having those 5, 10 connections that push more than what LinkedIn has right now?

Okay, rebrand, rebrand your tagline. This here, you want to have meaningful connections who can actually help me get to where I want to be versus have 3,000+ connections on LinkedIn who are absolutely useless and won't help me in any way except for boost my profile to say that I'm connected with XYZ person.

Exactly.

What would you say would go wrong with investing in a startup like this? What's like the risk involved?

I think considering we don't have that, our expense plans are not that high, I think the downside is relatively low. I think the biggest risk is that, you know, there's fundamental errors with the startup's market fit, but I think we're seeing enough market validation that's not even really a concern. People are asking us to build this.

Yeah.

To build this.

Well, big issue is, it's a consumer platform and the issue with it is always not getting enough people on it. I mean, LinkedIn has a billion and a half users. I don't know how many of those are actual users, like 200 million or something. Maybe I've, I obviously don't have the exact numbers, but the issue would definitely be pushing the, the consumer platform high enough so that millions of people and hundreds of millions start using it on a normal basis.

So to summarize it, what would you say would be the risk involved?

Bringing the number of consumers to the point where it just goes viral and everyone starts using it as the new go-to platform.

At the same time, we built this to be as, we've built this out because of the amount of validation we've gotten. And the way we've built this and what we've already designed has made this, I think, as low cost as possible. So it's a relatively low risk investment at the same time.

Yeah, it's true. Yeah, we don't need massive investments for it to, for the platform to work.

What would you say the future of AI looks like.

I mean, AI has so much power to change the world. I think it's kind of a universally known truth right now that we're standing at this technology that is fundamentally reshaping the way we're doing business, the way we're building things. And we're getting to the point where it's, I think, it's creating a fundamental change in the way people are interacting. And I think that the important thing is to make sure that when we're building these tools with AI, we're building things that prioritize the human experience and human connections rather than automating it away. And that's our fundamental goal with this project is to use AI to further connection rather than to use it to replace connection. And that's something where I think we're seeing in society and are worried about. So that's part of why we're building this.

I have to ask, what would you guys say, what would your legacy look like or you want your legacy to look like?

So I think I was talking earlier about this attention economics on LinkedIn, this idea that everyone has to kind of make themselves as known as possible on this platform to get as much reach, as much outreach. It's something that's not unique to LinkedIn. It's on every major social media platform. And the goal here is to fundamentally change that way of thinking to instead be, okay, who are the people I'm— instead of thinking about talking to as many people as possible, to be as close to as tight of community as possible. And that's our fundamental goal is to reshape the way technology builds communities, both professional and personal.

The fact that you guys have this legacy in mind, because that ultimately decides how you guys go about building, scaling, slash being successful at what you are working on right now. One last question. Is there anything that you guys wish I asked you but didn't?

Any questions you didn't ask? Well, what else would you have asked us? Maybe we can answer any last and final thoughts you have.

I mean, just any final thoughts that you have. I think I can't think of anything, to be honest, aside from— Yeah, I can't think of anything else.

One thing that's kind of fun to talk about is our logo. We kind of zoomed in on— it's supposed to be two coffee beans, and then it ended up being one coffee bean. Now it's like a very zoomed-in picture of half a coffee bean.

It's like we might have spent a bit bit too much time on the visual aspects of the logo then rather than just coding away the project. I mean, it didn't take too much time, but still, but just like maybe really thinking the logo through wasn't the smartest choice.

Also, I think that's half the fun of building a startup. You got to make those decisions, you know, the name, the domain, the little things are always quite fun to do. Keeps you going.

I see. Like, I mean, and now that you told me what Dope Your Labs probably stands for, it makes complete sense why those coffee beans. But also, I feel like, I mean, yes, you, you always feel like you could have used that time to work on something better, maybe make your website better, you know, do something better. But honestly, I feel like as long as your website seems, you know, user-friendly, appealing, and as long as people resonate with the logo because I don't know if people on your platform really speak Italian or understand what this name really means.

Yeah, neither of us do.

At that point, it's more for us than anything else.

Then I think that answers your question, why you spend more time on that.

Yeah, that was fun.

Yeah, thank you.

Of course, great conversation.