Jim Groff & Paul Weinberg: Inside Dokkio’s Mission to Organize the World’s Information

All right, welcome back to the Casey Adams Show. Today I am joined by Jim Groff and Paul Weinberg, the co founders of dokio. Thank you so much for coming the show today, guys.

Glad to be here.

Our pleasure. Thank you.

Of course. So for the context for the listeners, Paul, I know we've known each other for a handful of years now, and diving into your story and understanding what you've built, companies and acquisitions, you know, it doesn't surprise me about what you guys are going out to build at Dacio. And Jim, you know, when Paul brought up yourself and Dakio, I was really excited to dive into this conversation because, you know, a lot of the interviews that I'm doing nowadays not only correlate to AI, but just the, the different perspectives, especially with people that have built and grown and sold companies, I think is very fascinating of just like where AI and the general opportunities lies today. So first off, I want to say thank you guys both for being here today. And Jim, I'll go ahead and I'll start with you. For people that may not have context on what Doc I.O. is or your background, we'd love to start there before we really dive into the conversation.

Sure. So we solve a problem that in my experience, when I start to describe it, almost everybody nods aggressively and that is we're overwhelmed with information and it's scattered all over the place. The stuff I need to do my work is in email, it's in Google Drive, it's on my laptop, it's in Dropbox, all over the place. And if it's just me, that's a problem. If it's a team of us, that's even worse. And so that's the problem we tackle is how do I get my arms around unified view of all that scattered information, an organized view. And with AI now, a point of view of that on that information that I can understand.

Absolutely. No, I love that. And you know, I, I want to go to you, Paul, and I know you both. We said it, we were talking before we got started here. You guys go way back in terms of working together as partners. And, you know, I want to ask you, Paul, you know, how did not only you guys initially meet and start working together, but how is it different this time around with Docio?

Okay, well, I won't say how many decades ago, but we met at the very, very beginning of my career, first real job out of graduate school. It was a small tech company in Silicon Valley, and I was young and immature and obnoxious and bounced around within the Organization in a few different roles before Jim said look, hey, come work for me. And we started working together where I worked for him. We ended up writing a book together that ended up becoming a bestseller. We ended up deciding that not only did we work well together, but also had Jim had an idea and a vision for how to create what was called, what was it? Work group computing.

Yeah.

Before they had the Internet, before they had client server everywhere. And so it was a big deal. We left the company, developed a prototype, got a large first customer and built that company over the next few years and sold it to Apple.

Yep.

That is.

Jim was more suited for Apple than I was and spent 10 years there. 10 years. Ended up running the education division with billion dollar P and L responsibility. I ended up moving down to Los Angeles and partnered with a gentleman with whom I'm working on a different company. But Jim and I have stayed connected over the years. We've been partners on and off. We wrote a second book together. It was also a bestseller. And then he got involved with what he's doing today and I got involved in being his partner again. I'm not running the company, I'm not involved day to day.

But we catalyzed the idea for what has become Dacio. Very much together and very much together with more recent partner of Paul's, Ariel. And the three of us really catalyze the idea and have driven it.

That's amazing. And I know Paul, we've talked about the previous conversations just building and selling a company to Apple, especially back in that era and seeing obviously how Apple has grown into the company.

Here's how I date us. We were the very first acquisition by Apple.

No way.

Ever.

Wow. Maybe for. For you, Jim. I love the entrepreneurial story. Take us back to that first acquisition by Apple. Where was Apple then? Why Apple? And bring us back to that time of you both working together and what it ultimately led to, you know, not only going to Apple, but that experience.

So what the what? The product that we built was connected PCs and PC applications with corporate databases, corporate data, corporate data up there, locked away in the data center, hard to access, etc. I had helped the very first group inside HP to bring our first personal computer to market and so had a fair amount of sort of front row seat experience with what PCs were and how different they were in terms of accessibility, usability, immediate productivity, et cetera compared to the corporate data center. So the product that we built linked those two worlds together. We actually approached Apple as an investor. We had bootstrapped that company. The two of us again, grew off of the early customers that we had and said, you know, there's an opportunity here. We need to bring in outside investors. Had a Tier 1 Silicon Valley venture capitalist, the leading company in the PC database market at the time. And Apple prepared to co invest. And then Apple started to ask us about Mac first. Mac only, Mac better. And it's kind of like, you know, timeout. You're a third of a group that's trying to buy a piece of the company. That doesn't happen. These other two guys don't have the same goals. So either we need to replace you as an investor or this transaction needs to be something different than an investment. And 11 days later, it was an acquisition.

11 days later, yeah. Wow.

I mean, we, it happened, it happened fast. They were, they were very decisive. But there was also a, there's also a backstory about why they were already familiar with our company at the very highest levels. John. This was the period when John Scully was running the company. It was the interregnum between Steve Jobs, who then got kicked out, came back. John Scully was running the company. And I was on my way to Toronto for a business meeting.

Okay.

And I'm standing in the line and waiting to get to the ticket counter and who's two or three people ahead of me? John Scully. So he gets processed, he moves away. I got to get up to the counter and I say to the woman, is he on my flight? And she said, yes, he is. I said, could I sit next to him? She said, well, he's in business class. I said, okay, I'll upgrade. And she put me next to him. Coincidentally, I was sitting next to John Scully for five hours.

Oh my gosh.

And we had a long, in depth conversation about what he's up to and about my company.

I don't say this often. That just gave me the chills because I think there's so many elements just to keep in, like take a step back, which I love kind of finding in these conversations is, you know, finding opportunities and striking when the iron's odd and doing things that are unconventional. And I'm curious to know, Paul and Jim, like, where have you found or have historically had opportunities like that where you've, you know, maybe it's upgraded the seat to sit next to someone strategically or, you know, like, do these things that are maybe unconventional to then put yourself in a position to win. And I think there's so many, like, examples of other founders that I've had over the years. And I always Feel that it's the, you know, where those come up in your journey is very fascinating and I love exploring those. So if none come to mind, no worries. But I'm curious if there's any parallels to that.

It's absolutely true. And in terms of the dynamics of the two of us working together, Paul is that guy. You know, partnerships work really well in my experience, when there are complementary strengths. And Paul is that guy. So that Paul, that's a question to you?

Well, I, I don't have any other specific examples, but I will say that Jim once drew a picture of how my system was wired. I probably still have it. I could probably find it. And it was a picture of one nerve connection from my brain to my dialing finger.

Because I would say, absolutely true.

Why don't we call Larry Ellison? And I'd be pick up the phone and I would start dialing. He said, what are you going to say to him? So I was sort of the knee jerk guy.

I love that. And I think any great partnership, right, Strengths and weaknesses, it's like, you know, your strength, you lean in. I love that story though. So you upgrade, you talk to John. App one's a buying your company first acquisition. They did. And I think this is a great sort of connection point to just what you all are building today with do and you know, Apple historically, right. You hear even today in terms of AI, like they're assessing different AI companies, AI strategy. And I want to take a sort of a step back and to kind of change gears here regarding do. When did AI become a huge part of your life, career from the business perspective and then also from the more like business opportunity perspective, building in this space specifically because, you know, there's I obviously, I'm sure as you guys have built in the baths, like AI was this underlining thing that maybe businesses would use or know that's coming soon. But now it's so at the forefront where I think on this show it's about weeding out the things that are maybe bad or trends versus the real meat of the impact AI is going to have in the business world. So I'd love to get. I'll start with you, Jim, the context of when AI not only came up on your radar, when it became important, and then when you, you know, wanted to go build a company within that state.

That's actually a great question. I would say we have been in the business of helping people make sense of and organize scattered, disparate, disorganized information for a long, long time. Long before AI came on the same, on the scene as sort of pop culture, but starting, I would say, three or four years ago, it became apparent before ChatGPT, but if you just read the, read what was going on, it became clear that AI was becoming ready for primetime and that it was going to play a major role so that we could actually fuse and combine together the sort of more conventional software approaches to making sense of this disorganized world with now an AI based approach to making sense of it. And they really are very different. Really are very different. The AI that we have to get today is all language based. It's based on patterns in language. You know, you probably heard the sort of trope, you know, predicting the next word. And it's amazing how far predicting the next word has gotten us. Well, that's true. So it's marrying that with the traditional, okay, we want to understand for this given account how does their, how does their business work, how do customers work, how do products work, etc. And that's what we traditionally built. So it's fusing those two things that really is a secret sauce.

I'll, I'll add something to that, which is that it's, it's fusing structure and lack of structure. I mean, natural language is as unstructured as you can get. What we've been doing for years with Dokio and my last company was actually all about structuring data beyond simply structure in a relational database table. It was relationships between tables, it was hierarchies, it was taxonomies. So we have a lot of experience with structure. Jim has a lot of experience with data management as well. In fact, the second book we wrote was on SQL. It was a complete reference on SQL, the structured query language that underlies virtually every DBMS today. And so what's going on now is marrying all the history of Dokio around creating structure from all these disparate places, pulling it together and then being able to access it in a very structured way around business concepts like customers, prospects, or if you're a law firm, matters.

Clients. Right.

The analogy is similar to what happened years ago when search was a big deal and ultimately Google search became the champion. Right. One little box, no forms to fill out. Yeah, you type it in and you get the results very quickly. There was just one problem. 1 billion, 400 million results in 0.87 seconds. And I don't want 1 billion results, I want three results. So what I did at my last company is similar to what we're doing at Docio. Which is add that structure. So instead of just getting blah, blah, blah, you get very precise, very targeted information. Yeah, it's really the information, the difference between data and information and taking it one level further knowledge.

Absolutely. One of my personal, I guess you could say, favorite ways where AI is being disrupted, as you mentioned, even on your end, Paul, is when you talk to ChatGPT, the change of SEO and how things are coming up in chat and how you have to optimize this new way of getting in front of people. And I want to talk about, you know, what you, what you all talk about with Doc. You have a contextual AI that understands your, and organizes your private content. I think there's one word that is just so apparent in every conversation, just context. Right. Whether that's context and the integrations that, you know, software can pull from, I'm curious to know from both of you and I'll start with you Jim, of like, why is context important? And like, given the, like, how fast AI is moving, like how do you think about context regarding a product like yours from these different data sources and how does that change over time? Because things, especially in this space today, move so fast and change so fast. So love to just get your understanding of context, why it's important for businesses and why it's going to be more and more important in the future.

Yeah, well, it's especially important if what you're trying to understand and work with is private content. If it's your emails, your files stored in Google in Google Drive, your content stored on your own, on your own laptop. If you think about the, the Chat GPT and what everybody understands as quote unquote AI today, the large language model that underlies Chat GPT understands all the nuances about the structure of language because it's been trained on the entire public content of the Internet, number one. Number two, it understands all the facts that are stored in the public content of the Internet because it's looked at all those billions and trillions of pages. What it has no clue. So that provides the context for that large language model to understand what you type to it. If you ask that chatbot about your own private content, if it's honest, it'll say, I don't know, if it hallucinates, it'll make something up. Right. And so the context of my own private content, how does it relate to the important pieces of my business? What Paul was talking about, my customers, my products, my prospects, orders, shipments, etc, that's the context that we add and it's, and it's critical. Without that, it's just a bunch of, just a bunch of language pattern matching.

Let me add to that. When you, Casey, you brought up the word context. Jim, you elaborated and talked about private content. What we do is complement what the chatbot does. Yeah, Chatbot knows the population of Peru. It can tell you what's wrong with our political system, but it doesn't know anything about my business, my files at all. So the marriage here is give it context, but it already has context for the world. It just doesn't have context for your private information. So what we're adding is a plugin into the chatbot that allows the chatbot to know as much about our stuff, our private stuff, as it knows about the rest of the world. Now, you could say, well, eventually they'll just have the chatbot be able to do that. But people don't want to do that. It's my private content. I do not want to train the public LLM, public chatbot on my content. The beauty of what we do is that you're. Your private content remains private. It isn't used to further train the LLM. And that's sort of what we think is the huge innovation. Lots of structure, full context, stays private.

I love that. And I mean, I think it's so important. And, you know, there's a couple things I want to hit on there, but one thing that I saw came out recently where I think they're, if they're changing it, where OpenAI, it's pretty much like, hey, like anything you've typed in, this, like, public chatbot is like, it's public. And if, if anyone ever wanted to use it against you in core, like you could. And like this, this idea of privacy in this era, especially with personal information, is so important. And we'll get to that. But one thing that you mentioned, Jim, is all things hallucination. Hallucination with AI and this is a concept that I've been listening to and hearing about on different shows. And I would love to spend a moment on it because I think it's, it's scary, right? People can go through these, like, hallucination loops of like, false information and believing your own narrative. And, you know, I won't try to butcher it in my words, but like, what is a AI hallucination? Why is it important? And why should people care to have. And knowing about it?

Well, underneath the chatbot, underneath the conversation, the large language model, say, from OpenAI, but it's true of all the large language models, is just doing very sophisticated pattern Matching around the language. If there's a plausible answer to the question that you posed that works as English language and there's nothing else obvious to do, the chatbot's going to give you that answer whether it's anchored in the facts and reality or not. Now the large companies like OpenAI, like Google, et cetera, have done a lot of work to try to tone that down and eliminate that and that's great. But when it comes to again, asking questions about your own private content, it doesn't have a basis to understand that. So the choices, in a very real sense, the chatbot has two choices. Admit that it doesn't know or make it up.

And that's the hallucination of making it up.

Well, and not only that, making it up and asserting it with confidence.

With confidence.

Right.

Yeah.

These chatbots have gotten very sophisticated and nuanced in terms of their understanding of language. So they will answer that question, as Paul said, very confidently, very clearly, in a perfectly formed sentence. That's wrong.

Yeah, Yep.

And so I mean the advantage of what we do is it's all grounded in Dakyo. Having looked at your emails, your files, your documents, the content, the web pages that you visited, the content that's on my laptop and it, and it grounds the chatbots response in that information and basically wipes out the problem of the chatbot hallucinating. If there's content there that answers your question, it'll find it.

Yeah, absolutely.

Would now be a good time. We have a two minute demo video.

Please.

It illustrates a lot of this would now be a good breaking point.

Please do share the screen and for people that are listening, you can watch this on YouTube or Spotify to see the demo live. Paul, it'd be great if you could pull up the demo on your end so that we can have a better understanding of what Doc IO is in the demo.

Okay, here we go.

Lets take a look at how docio AI helps our friend here cope with the morass of files, messages and web pages needed to run their family office. He'll use the Docio web app as well as the browser and chat extensions. The Docio web app is connected to all my different sources of information. Three different email accounts, cloud storage accounts, even a folder on my laptop. Each its own separate silo. But docio gives me a better, more unified view. Here's an integrated list of all my investments. One click zooms in to all my information about Nvidia, wherever it may live. My partner calls and asks about our real estate holdings. One click pivots to the same kind of list. Pulling together all that information. I can do a global search to look at the research we've been doing on a potential Microsoft investment. Again, all pulled together in one place. I can even search images regardless of what I do. Always a focused, contextual, unified Docio. You don't have to be in Docio to use Docio in the browser. Docio augments this Google web search with results from my private files and emails.

That's really cool.

Web search results. Docio automatically summarizes it for me, tags it, and shows me related content. If I ask a chatbot a question about our deals, instead of this big fail, Dockeo MCP draws the answer from my private files and emails, giving me all the relevant information, all while preserving the privacy of my content and not using it to train another AI engine. To summarize, Dokio understands your scattered and disorganized content, organizes it into knowledge, and puts it at your fingertips wherever you work. Check out our website to try Dokio for free.

Amazing. Well done. That was a great demo.

I get about one or two phrases into describing that information morass that was at the beginning of that demo. And I get, you know, the person I'm talking to wants to finish the sentence for me and describe their own personal information. Chaos. So it's a problem that's broad and it's broadly acknowledged and in many ways we were doing a good job of solving it before, but AI has really catalyzed things.

Yeah, no, I mean, Paul, I appreciate you showing that demo. It's so helpful when it comes to context. I think the comment of a word or video can say a thousand words. I mean, having the understanding of private data and how that can appear even when you're not on the application. I think that was the biggest thing that stood out to me of if you're searching on Google and it can showcase based on specific instances of context from a file that might be relatable. Very cool. A question I have is from the use case perspective, individual consumers, businesses, where is the primary focus now and has that changed from early ideations? Obviously, if people are listening to this, whether they're hyper into AI or just a consumer that uses ChatGPT, the consumer use case is one thing, but then once you add the consumer enterprise business data on top of it, it's a whole different juggernaut. It feels so curious to know the use case today and I'm sure other people listening are as well.

Yeah, so we have a large user base who Are individual users. Right? I have this problem personally for the content, either my historical content, family stuff, work stuff or whatever. I would say it gets to be a lot higher value when it's a team working because they share the knowledge, the AI develops an understanding of their business, what the team is doing together. And that's a sweet spot for small teams, especially professional services firms. If you're an agency, if you're a consultant, you do what your clients ask you to do and that inevitably makes you disorganized, multi platform stuff all over the place. And so our experience has been those users have the problem that we showed at the very beginning of the podcast in spades.

Yeah, that makes a lot of sense and from the context. And this is for you, Paul, with Docio. I'd be curious to know yourself, your team and use cases that you've seen that have kind of stood out to you, that maybe other people that are watching or listening, maybe I want to say unfamiliar with or the. Yeah, the benefit of connecting all this data and how you all see the future of like these different data endpoints for Docia overall.

So I may be the worst person on the planet to ask because as far as, as far as I know, I'm the only person who doesn't use cloud based storage. Who doesn't.

We did talk about that. That is a whole topic.

Every single file that's ever sent to me in Dropbox Box or Google Drive, I pull it down to my laptop, I create a folder, I name it, I rename all the files and I'm caught up. So I'm actually not a typical user of Docio because I put in all the time to curate my files, to rename my folders, to reorganize, to make sure they're not duplicates and so on. I know in the. That's easy because I'm, I'm sitting at my desk and I have control of my universe. Most people don't have that. And in a corporate environment, when you have a team, you certainly can't enforce it on all the other team members. So. But in my own world, I'm master of my domain, as Jerry Seinfeld used to say. I never saw a single episode, so I don't even know what that means.

See, I gotta see, I gotta ask. This is more to like, to double click that. Why is that the case in terms of no cloud storage? And do you see that changing or is this a, I don't know, the personal perspective that you'll stick to forever?

I like order okay, so I'm not ocd, but I am anal. And I like order and I like things structured a certain way. Things have to be straight.

Things have to.

They have to be properly named. They have to have dates on the file names. But it's a lot of overhead.

Yeah. How much storage you must have terabytes and terabytes of or whatever.

Well, that's a good. That's a good question. About a month ago, my one terabyte disk was starting to get pretty full, so I went in and installed a two terabyte disk. No, actually, I installed a four terabyte disk. I think that'll cover me for the rest of my life.

We love it. We love it. Well, Jim, before we continue on, what do you think about that? I'm sure you've had conversations with Paul about that.

He is our worst possible user and, you know, there you go. But no, it's, it's, it's. It's interesting. I mean, all of those characteristics ring true, and they've been true Paul forever, Right. Ever since I've known him. And I think that in many ways informs the yin and yang of a partnership here. I mean, when we used to actually both code together, the first product that we did, you know, it's just a bootstrap. So you write the product at night, and during the day you go out and you try and sell, Right? That's what you do. Live it, you know, working out his spare bedroom to get it. To get it done. And so coding together in that environment was an adventure and a half. I mean, you know, Paul wanted everything lined up just right.

It was. It was unbelievably productive and effective and collaborative.

Absolutely true.

I love that when Jim was. Jim was laying a thousand lines of code breadth first, I wanted to go deep on every little thing because I just. I wanted to get the UI right, for example. But it worked very well for the prototype. And then as. As we went a little further and still before we had hired any people, we were no longer sitting together coding. We were sitting at two different personal computers, each coding different stuff. And he was doing the hard guts internals, assembly language, and I was doing the ui, which was.

Yeah, but those, those characteristics are true even today, decades later. Right. In terms of the way we tend to approach things. And what I think this is true of a lot of collaborative partnerships that are productive is those you find a way to fuse those two different perspectives and stop just shy of killing one another and make it work.

Yeah, of course. I love that. And I think we could have a whole tangent about all things. One thing that comes to mind that I do want to bring up is when it comes to the current use case customer base of Docio and for the people and listeners here today, how has your approach changed? Where does the company look like today? Team wise, feedback wise? What have you all noticed when it comes to getting teams individuals on this? Maybe things that come up often that make you think or use cases you didn't expect or just since it's been out there and users are on it. Like what's been the general thesis the last year or so?

Yeah, so you asked a couple of different questions. We've kept the team very small and focused because that's the key to them being productive. I would say the biggest thing that has changed in the last five, six months is with the chat interface now available, we when users say sure, you have permission to look at what I've asked the chatbot to improve the quality of your responses and we're very gratified. About 40% of our users give us that permission to look at their content. We're now much closer to seeing the quality of what the product actually delivers for users. Yeah, and that's great. I mean to be able to get close and look at actual interactions, actual use cases and see where did it fail again with the user's permission? It's huge.

Absolutely. No, that's amazing. Any thoughts on that, Paul?

I've experienced the same thing with the meticulous, the ability to get very close and get very real feedback on how the product's being used and how to refine it.

Absolutely. One thing that I do want to bring up is with what's been happening the last handful of months of companies like Meta making these massive AI super intelligence labs and the pace in which teams and companies are moving and how much capital is in this space. How do you all think about the. I don't want to just say competitive landscape, but other companies products out there just from like a overall state of AI and how that translates to internal team discussions. Because I love the small, efficient team aspect of where the world is going, where you can kind of make a team of four or five feel like a team of 20 to 30 just in terms of all these AI applications and especially advancements in just coding overall. But curious to know both of you and I'll start with you Paul, General POV on AI landscape today. Is it a bubble? Will we see massive changes? What's your personal thoughts on kind of where we are as an industry. And as a category.

Well, have you seen Terminator?

Indeed. I actually just had a humanoid robot CEO on the show recently.

Okay, very nice. So I think AI is not a bubble. It's been, it's been two years away for the last 25 years and it finally arrived as Ariel. As Jim said, it's now ready for prime time. It can't do everything. It hallucinates and it especially, it's especially bad on your private stuff. So where is AI heading? It'll get better. It'll be more willing to admit when it doesn't know something and that will continue. They're throwing thousands of people and hundreds of billions of dollars at it. So you can be sure that it's going to have an impact. It's already having an impact. People are losing their jobs. Models are now being replaced with virtual models. They can do almost anything in film and product. That was actually one of the issues with the recent strikes around the use of likenesses. So it, it's definitely having an impact across every aspect of society.

Absolutely.

Now having said that, how does that impact us as a small team? I think what's true is that large companies have been buying small companies since the beginning of time because large companies can do some things very, very well and they cannot do other things well. And in particular they can't do what's the express, you know, green screen or what? Basically they can't start from scratch with something completely new. Yeah, either because they don't have the.

What'S that like the zero to one mentality.

Right. They, they either don't have the vision or they already have entrenched groups.

With.

A stake in preserving the status quo. So for example, Jim's second company was a company called Times 10 that was acquired by Oracle. Why was it acquired? Well, they had developed the fastest in memory database on the market and they were eating Oracle's lunch. If I'm not mistaken, Oracle had its own main memory project and ultimately when it looked like Jim's company was going to get swallowed up by another company, Oracle decided to buy them. So their Oracle's main memory product that's on the price list as a checkbox is a product that Jim's team, Jim's company developed. Similarly, when Ariel, who Jim alluded to earlier, and I were building the company that was acquired by SAP, there were about 150 companies in the space. There were only two who had any real traction, us and another company that was really strong in sales and marketing. Product was weak. When the other company was acquired by IBM. SAP saw the handwriting on the wall and they decided they had to have us. And that was despite having an internal product that had probably 800 people invested in it. So when you look at SAP's Master Data Management product, their MDM, that's our product and it's baked into their DNA because. Because many of the other tools, the SRM, for example, use our platform that they acquired from us as the back end. And so Jim's main memory database still on the Oracle price list. And 20 years later at SAP, they've built a billion dollar business around the software that they acquired from us.

That's amazing. And I think just to again double click that comment, something that's been very weaved into this conversation, all things M and A, packaging, positioning companies, buying the ticket, putting yourself in a position to win. Would love to kind of take a step back. And for the founders that are listening to this, that are building companies, whether they're AI tech companies or just any other type of venture, I'd love to start with you, Jim, but I want to ask this to both of you is what's your biggest piece of advice to founders on packaging and positioning a company for acquisition in specific markets, given you guys have not only done that one time, but many times over and not just have had acquisitions, but successful integrations, which I think is a whole other conversation where we could go on a whole other podcast around the implementation and staying power of a product in an organization like you both as just Paul, as you discussed there. So I'll start with you, Jim. Just all things M and A and your thoughts and perspective there.

Yeah. The advice I would offer is build a real product that meets a real need for real customers. Make sure it's visible and then you're in the right place, you're in the right position for where the market is going to evolve to. I think, you know, the landscape is littered with companies that are, have been built with the idea of, well, we'll build this thing really quickly, we'll get it ramped up in nine months, 12 months, we'll get it sold off and make a lot of money. You know, the staying power of building something real that's delivering real value is the key to getting when an acquisition makes sense, to having it be done at high value. That'd be my advice.

Yeah. And how about yourself, Paul?

So Jim touched on much of this, but basically philosophically, you have to plan on building a company, a successful company that is going to go to market, have revenue, have a P and L And be for real. You can't build a company planning to be acquired. So build a company, you know, what was it in Field of Dreams? Build it and they will come. Yeah. But don't plan on it happening at a particular time.

Right?

Yeah, that makes total sense.

And none of what Paul or I just said contradicts the fact that in many cases the outcome is going to be an acquisition. It's a very, very, very small fraction of that manages to build something that's IPO worthy, that can survive as an independent company. The much more likely outcome is an acquisition. But you don't aim there. That's the desirable byproduct of building a real product and a real company.

Absolutely. I love that perspective a lot and I think we could talk about that for many, many longer. Discussion. One thing that I love bringing up that I think is extremely relevant to this conversation is for both of you, for what you're building at Doc IO, what excites you both the most in regards to the product today and the use cases into the future regarding what you're building and the implementation for your users. And I'll start with you, Jim.

Yeah, we're still very early on the learning curve in terms of what ways that users are finding to productively use what we deliver. That's what's exciting to me. I'll give you example. We have a teacher in the Pacific Northwest that uses the product. It's the time of year when you redo lesson plans, you redo syllabuses, you redo student prompts for the first few weeks of school. We never would have had any of that in mind in terms of what we were building. And yet to see that come to fruition and have the intelligence and all that taps what he's already got. He's been teaching for a couple decades, so it taps into all that he's developed, but again uses modern AI to update that for a new school year. It's just a concrete example of what's very gratifying to see, frankly.

Absolutely. I love that. And how about yourself, Paul? What excites you the most in regards to what you're building at Doc IO and the impact of the product?

Well, I'll defer to Jim in terms of his real world examples. But what excites me is that you finally have the holy grail of file and beyond file Message and Content management, which is a complete integrated view of everything that's semantic so it understands, it knows, and so you can search in a variety of ways. Now the AI takes it to the next level as Jim was describing with his example. But for 30, 40, 50 years they've been trying to come up with this semantic file system and I think that's part of what we deliver at Docu.

Yeah, I love that. And you know, as we start wrapping up this conversation, I'd love to ask you both, you know, when it comes to the use case and implementation of how people listening or that are still watching this video today, where's the best place for everyone to not only learn more about the product but start using it for their own, you know, file data management and just really give it a span overall? And of course to provide you and the team feedback on it.

Sure. Well, we have a premium product pricing structure so below a certain tier of how much you try to connect up and it's a pretty generous level product is free. So you go to www.docio.com and sign up, connect it up to your content and get going. We try to make that process as short as possible. It does take in some cases if you're connecting tens of thousands, hundreds of thousands of files and emails, it can take a couple of hours for it to come down the learning curve and understand if you're just have a few hundred, it's going to do that very, very quickly. But go sign up, try it out for free.

Very exciting. I and I'll, you know just my final thoughts here as well. You know, when it comes to the people, listeners of this product, excuse me, of this show, if you are listening, make sure you please reach out to myself, reach out to Jim Paul, after you give it a spin. I know, I'm so excited about this and just this idea of context and like the personalization privacy that you guys have built, very exciting, very unique and I just, I can't wait to have another follow up conversation like this in the near future to talk about how you guys are just taking over the world and helping the world become a better place. So as you are already so I appreciate you both so much.

Thank you.

Casey, you rock. Thank you.

Very true.

Appreciate it. Yeah. Thank you so much, Jim and Paul.

Take care.

Bye Bye.