Jake Aaron Villarreal: I'm Jake Aaron Villarreal, born and raised in Silicon Valley, and here to take you behind the scenes to share what it's like to be a startup founder, the journey they're on, the problems they face, the products they build, and an effort to make our lives better. I'm excited to have with us today Hans Guntren, the co-founder and CEO of Deliberately AI. Hans, welcome to the show.
Hans Guntren: Hi, Jake. Thanks so much. Great to be here.
Jake Aaron Villarreal: Well, thanks for joining. Where are you joining us from today, Hans?
Hans Guntren: I'm at our headquarters in San Francisco, California.
Jake Aaron Villarreal: I love that area. I love San Francisco and so much innovation going on there. Um, are you originally from there or what, what brought you to SF?
Hans Guntren: Uh, I'm not. I actually grew up in the Midwest in Northern Iowa. I was a small-town kid, but uh, I was, I was always excited about computers, technology, and the internet. And uh, made my way out to Silicon Valley in 1999.
Jake Aaron Villarreal: Awesome. Good time to be out there. It was the dot-com boom and god, everything's evolved since then. What shaped you into getting more into the technology and the product side of things?
Hans Guntren: Yeah. Um, I've, I've always been a maker of sorts, uh, and I uh, studied design in, in university. I've always enjoyed uh, the solving problems using whatever, you know. In the physical world it's physical things, but in, in the software world it's user experience. Silicon Valley was kind of the intersection of, of design and technology for me. So I, I entered the field as a, a product designer way back in 1999. It wasn't really a formal practice. Uh, it's evolved quite a bit over that time, but um, I started out just wanting to make products and figure out how to, how to give the users of them, whatever they may be, um, a great experience.
Jake Aaron Villarreal: Yeah, it's so important even for products that are not technical. Just that user experience really makes you remember it, want to use it, want to talk about it, and ultimately solve problems that matter. I think you know, in today's world you don't need to really be engineers to develop things. It's really the, the product mindset, the user experience mindset to 'can you solve a problem and bring something to market' and in some cases don't even have to really engineer them. It's just using the tools that we have today. So exciting times since, you know, 1999 to today. Lots of, lots of transformations happened since then. But we want to talk today about your experience in the startup world and the company that you are building today. So before we jump in there for the audience, walk us through a little bit about your trajectory and your career track. Did you start off in enterprise, in startups, in, you know, mom and pops? Give us a little background there.
Hans Guntren: Yeah, you nailed it. I've always been in the enterprise space and generally speaking, I've always entered into early-stage companies. That's the, that's my happy place. I think I like the dynamics of it. It's very, it's very fast, very fluid, and you know, oftentimes you have very direct access to the, to the customer, which is very important when designing product. I set out early in my career joining an early-stage company that was acquired, uh, was acquired, and then that company was acquired. So I went quickly from very small all the way up to IBM. So I got, you know, in my first couple years of career, the full spectrum of, of career experience and really, really sort of got to learn what it takes to take a company from, from that young age through to fruition of some sort. And after that I, I went back to a startup, repeated that process again, went through another acquisition. Uh, and then I, I set out and started advising companies.
And uh, for about 10 years I was essentially a virtual chief product officer helping very early-stage companies go from idea through to having, having a fully-fledged product. And that was a great experience in terms of learning the ethos of a, of a founder, what it takes, how those people think, and how they get things done. And that journey led me to uh, an early-stage company called C3 AI, which I had, I had some former friends and colleagues there and they invited me in to help them on the product front, and it's a great space. Even 10 years ago while AI wasn't LLMs, it was mostly machine learning. I could see the writing on the wall. There was a huge opportunity to go in and help industries that are behind the technology curve modernize, become more efficient, more effective in what they do. So we served almost every imaginable industry. Things like healthcare, manufacturing, oil and gas, aerospace, Department of Defense, financial services. Got to, got to go into all these areas and kind of see where they're at and then dream about how we could take the, the large datasets that they have and mine them for insights and help them run a better business.
Interestingly, about the only, about the only industry that I didn't touch during that time was legal services, but I went through a divorce. I was married and went through a divorce right in the midst of this career where I'm transforming industries. As someone now working uh, in the legal arena, I could see all kinds of opportunities uh, to make that process more efficient and effective for the, the client, myself, the end user. And I like fixing things. I like, and I like helping, helping people. And I put that on my list as a, as a great area to, to go into at some point down the road. Um, a couple years ago after leaving C3, I was thinking about what to do next, and it was, it was a really great time because LLMs had, had just come to the forefront, and this is where the idea for Deliberately AI came. It was, it was the intersection of LLMs and my desire to, to build something that would help optimize the way that attorneys and their clients work together.
Jake Aaron Villarreal: Wow. Well, you've set the stage pretty well, and for most people that are building companies, it's always about looking for the problem that can be solved. Thanks for sharing a part about going through a divorce. Lots of us have gone through them and it's kind of a, a black box. You don't know what you're getting into. You don't know the process. You don't know how long it's going to take. You don't know how much money it's going to end up being. And, but that's on the user side. But you're really serving a problem for the, for the law firms. Is that correct? Like the, the technology for the law practices to be able to operate more effectively, more efficiently with AI.
Hans Guntren: Yeah. Yeah, that's exactly right. It started with me wanting to solve a problem for the, for the client. And the, and the real problem that I was focused on is, you know, when you're, when you're working on a legal matter, whatever it may be, it could be a divorce or it could be, you know, a tax issue or an immigration issue. Typically the, the client is a member of the general public and they're starting that, that case or that matter from scratch, and so there's a tremendous amount of documentation, facts, and information that need to be conveyed from the client to the attorney in order for the attorney to do the work they do. My, my initial perspective is that it was very hard for me as a client to collect all that information and convey it to the attorney. Many, many meetings and typically going back and forth via email and putting things in a Dropbox. You know, the process lasts a year, two years, sometimes five years for some people, and you're just continuously providing more and more information on your financials, your assets, your debts, your children, retirement accounts, they're all changing. You're always sort of conveying new information. So, I wanted to make that very easy.
And as I started talking to law firms, I quickly realized they have the same problem. Not only are they getting all that information from me as a client, but they're typically working with many, many clients. You know, it could be 30, 40, 50 uh, per attorney. Imagine if each of those clients has uh, dozens or hundreds or in some cases thousands of documents. These attorneys are sitting in a sea of emails and scattered information all over the place. They do their best to consume it and organize it and use it effectively, but quite frankly, it's impossible. It's impossible. If I send you a thousand-page tax return, you know, you're going to, you're going to find this or that that you need, and there's probably other things in there that could be valuable, you're never going to see them.
So we started focusing on the uh, space between attorney and client and we've built a platform that we sell into law firms that they extend to the client. And what it, the platform does is it starts collecting that information automatically. It's got a client-facing AI agent that has awareness of the law. It has awareness of the law firm and the things that are needed for the specific case type. And it starts interviewing the client and asking them questions that identify the shape of the situation. And as it learns, it knows where to drill down and ask more questions. It knows where to ask for supporting documents. And it makes it very easy for the client to add all that information in. It gives them a checklist that they can work against. Gives them a single portal where all their, their files and information are stored so they can see what's been provided and what's still outstanding.
And then on the attorney side, that allows us to do some really cool things. We behind the scenes consume all that information. We organize it. We read every page of every document. We map out all the entities that are involved in the matter. People, accounts, children, you know, all of it. Every asset and the relationships between them so that for the attorney we can do some really powerful things. First and foremost, we can summarize all of it. So, if you've got a case that's been running for eight months and there's 800 documents in it, the client's adding new things, you know, in the day-to-day, there's a real-time summary that reflects all that information for the attorney.
And this is very valuable even in a simple sense. For example, when the attorney wants to have a conversation with the client, they can go and read a summary of the whole case. That's much like the patient chart that your physician looks at just before they walk into the room and have a conversation with them. It allows them to be more informed, to give the impression that they actually know what's going on in the case, remember the kids' names and where people work. And that's traditionally something that's very hard for attorneys. Right before a meeting, they're oftentimes trying to remember, 'Oh, who are these people? What's going on? What's the context?' Uh, and that comes through. I could remember that in my own uh, personal case, kind of seeing that the attorney didn't fully always remember what I had shared. That erodes confidence over time. It's, it's hard for a client to see that.
We can, in addition to the summary, we can do a lot of other powerful things. We've got a um, a number of tools that are built into the product that identify patterns in communication. For example, oftentimes clients in divorce will upload three, 400 screenshots of text messages between uh, them and their, their spouse. Those messages would be very hard for a human to consume, to go and read and try to put them in order and make sense of them. Our system can do that automatically and then generate an analysis on, you know, who's the more cooperative person, who has issues around co-parenting, who's, who's harassing each other, you know, and sort of gives a lay of the land in a really complex way across all of your cases in, in seconds. That's, that's very powerful.
And then we also have an attorney-facing AI agent that allows the attorney to ask any question. And this is, you can liken it to ChatGPT for a legal matter. So you, you know, as an attorney, you can say, 'What are my, you know, what are all the cases where my client's spouse traveled to a specific location between the months of, you know, June and October?' And because we have access to let's say credit card statements, we can say, 'Well, looks like there are 17 trips to Miami where they are...' very powerful. That used to be a, you know, a process by which maybe a paralegal would go line by line in every credit card statement and try to figure those things out and build a spreadsheet. Takes months sometimes to do, you know, a really complex analysis. We can do that in seconds. And the thing we're working for, towards in the future is now also having the ability to draft documents with all that information because we've constructed a, such a detailed understanding of the case. We can ingest, let's say, a template for a settlement agreement or a contract, populate all the information based on everything that we know about the client, and that gives the attorney a great starting point to build off of.
Jake Aaron Villarreal: Yeah, that's amazing. Why do you think the legal industry's been kind of lagging behind technical innovation over the last 20, 30 years?
Hans Guntren: Uh, that's a great question. I think it's largely the nature of um, law firms. If you look at the industry at large, um, about 90% of law firms are very small. They're, they're 10 people or less. Imagine you're a small firm, 10 people. You don't have an IT staff. You don't have someone standing by to do integrations for you. You're just a bunch of attorneys and you're great at practicing the law. You know nothing about technology. And legal tech historically is very involved to um, to integrate. Can't just turn it on and have it work. It was kind of a structured thing where you had to have data tied to the right places and uh, you know, lots of configuration in order to, to make it work for bespoke types of cases like a divorce. The magic of what we're doing is we set out from day one to make this work out of the box and we can do that because of LLMs. The whole system is fluid. It builds in context of whatever the legal matter is that you're setting up. It says, 'Oh, I see this is a property law case. Let's get some, let's identify a list of questions related to property law and present those to the client so they can answer them and, and get that process going.' It's really as simple as turning it on and logging in and it, and it starts working for you.
Jake Aaron Villarreal: Really cool. You know, if you're someone at a law firm using ChatGPT today for legal work, where does it break and where does your product go further?
Hans Guntren: Mhm. Well, I would say that probably the, the bulk of GPT use uh, in law is probably related to, you know, legal precedents, understanding law history and interpreting the law. What we're doing is very different, right? We're, we're focusing LLMs on the client's personal facts and information, right? With all these bank statements and very sort of private information. You would never want to take, you know, let's say 250 client bank statements or tax returns and dump them into ChatGPT. First of all, it couldn't do that. But secondly, you wouldn't want to. That would be a very risky thing to just have your things out floating around uh, like that. Our system is built first on a, you know, a data repository that's very secure and then, you know, with an LLM sitting privately on top of that, right? So that um, it's all self-contained and the, the information, whether it's 25 files or 2,500 files, can all be understood by the LLM at once.
Jake Aaron Villarreal: Yeah, that's cool. You know, every company is going through this AI transformation or trying to figure out how to use AI. And I could understand in the law industry how it's so much data, structured and unstructured. How do we make use of it? How do we remember it? How do we add value to not just one customer, but repurpose, you know, our technology for multiple customers? And how do you do that well in an orchestrated way with, you know, agents and technology and AI? And sounds like you're right in the middle of building something that's very innovative and I can understand how law firms would want to be able to do something without having to build IT staff to do it. So really cool to see what problem you're solving there.
I want to shift gears a little bit to you as a leader. So you're building this company. You know, part of the challenge is finding the right people to do it. You're running a team now. Um, you know, a relatively small team but nimble. How has AI changed what a team your size can accomplish?
Hans Guntren: Well, as you know, you know, there are efficiencies that come out of it left and right. You know, I think of myself in the day-to-day. And it's clear that my output has increased dramatically. You know, in terms of producing content, social media, contacting people, networking, it's almost every facet of everything we do has been, you know, had some efficiencies add to it, added to it. I think, I think you know, you could probably do, you know, with a team of 15 people what used to take 50 or 60 people if you look across the board, whether it be marketing, engineering, you know, you name it, it's just everyone, everyone is making the most of the tools that are available and it's a fun process because honestly, we're, we're learning every day, 'Oh, there's a new tool for this or a new tool for that.' Um, uh, it's a, it's a really fun process.
The thing that's kind of interesting about it that I, I joke about is that, you know, you, you spend a tremendous amount of money to, to build and engineer a product in today's world. I often, I often joke that, 'Hey, you know, we're, we're going to invest a bunch of money to build this product over the course of a year or two years.' At the end of two years, you might be able to build the same product in 15 minutes through the technology that's available. But of course, that's, we will be riding that same, that same wave of acceleration, really no other way.
Jake Aaron Villarreal: Yeah. You know what has building teams taught you about hiring and especially in...
Hans Guntren: Well, it's, it's critical, right? The people are everything. We're nothing without them. All the, all the intellectual property that we have as a company comes from our people. Furthermore, the way that people work together is critically important. Building a, a really healthy dynamic, you know, in a place where people feel good and, and, and enjoy working with each other can be the difference between survival or, or failure. And I spend a lot of time focusing on this when hiring, especially at the early stage. You know, I think of it as um, you're essentially planting a seed. You know, think of it a seed for a tree. And then so the people that you, that you hire first, you have to be the most important with because they become the culture and the, and the leaders who go on to hire others and they hire typically people like themselves. So, you know, as you, as you bring in the first 10 or 20 people, that's your seed. And I think oftentimes the, the culture of the company is a reflection of how that, how careful you are in that, in that early stage.
Jake Aaron Villarreal: Yeah, it's really important. You know, we've learned, you know, I've personally interviewed 30,000 people in the recruitment side and one of the things that I've learned and our company's learned, excuse me, of the hundreds and, you know, close to thousands of companies we've been working with over 10 plus years now is there's really only two variables that you have to get right for success to happen when you hire. And there's a lot of noise of how to do it. And there's a lot of different ways to check and make sure that you're getting the right person at the right time and paying the right amount. But if you get these two things right, and I want the audience to know this, it's taken us a long time to learn it, is if you understand who you are, if you understand your identity as a leader and then the culture that you're building as a company and you're very clear on that, that's starting point number one.
The starting point number two is really what are you building for and who do you need to have to help build it. So the two things you need to know is who you are in your culture. Second part is, are you hiring the right person that has a competency to do the job if they align with your culture, and you got to interview. That's why the interview is important to kind of sift through that to make sure that they have the identity that you want. And culture could be um, how you operate, the pace you operate. Are you a system builder versus just a follower of systems that I have to, you know, implement, whatever your culture is. It's not just kind of who you are, but how you operate and then the competency of what they need to do to execute and succeed at their job.
You get those two things right, we've seen almost every company scale well with those two things in mind. It's hard to get lost in the shuffle with all the things you want to check, check off. You know, do they have the right this? Does she have the right that? But ultimately those are the two things if you really funnel it down to importance. When we look at companies that are you know, early stage we always ask, 'What's your identity? What is your culture?' And you'd be surprised at how many haven't really thought about it because you're just trying to build a product, you know? And so it's critical, it's, it's critical to do it. It's also critical to rethink it and repreach that internally so everyone's on the same page.
So, I just want to share that with the audience and also with um, anybody on the podcast because it, it will help you going out 18 months from now. Where do you want to be? What as a company do you need to close in terms of gaps of people maybe that you might need? This is kind of a free show to, to tell the world, 'Hey, I might need these people in the future. If they apply, it's free. There's no charge.' This is for you. What do you, what, what's your roadmap look like in terms of talent going forward?
Hans Guntren: Yeah, thank you so much. I agree wholeheartedly by the way. Understanding who you are as a, as a leader allows you to be effective in, in identifying that culture and finding the right people. In terms of where we're at today and where we're going, we're heavily focused on R&D. So, as you can imagine, software engineers, AI engineers, and I suspect that's going to be an area for continued growth over the next 18 months. Those people are surprisingly hard to find. You know, um, they're, you know, they're sought after by the, the biggest and best companies and we have to compete with that. So, we use our culture as a differentiator. It's a fun place to be and you get to work on world-changing things and you have a, you have a lot of latitude and agency here which is, I think, something that matters in folks who work in engineering.
Jake Aaron Villarreal: Yeah. Really cool. Well, join the club. We're also hiring engineers ourselves as we're building AI for our own company and you know, mapping out our GPTs and our agents and our roadmap to, you know, helping improve our efficiencies. Um, cool to hear where you're at as you look forward on your roadmap of building. What's uh, what, what's on the horizon latter part of 2026?
Hans Guntren: Well, 2025 for us was foundations. We laid the groundwork for the, for the product of the future and that's, it's been hard and, and also very rewarding. We now have a very solid data layer to build upon, you know, all the features that uh, that we want to have moving forward. We've got our, you know, our early-stage product. It's a uh, it's available. We've released it at the beginning of this year. It's out. We've, we're running in uh, law firms across the United States and even in uh, a few countries outside the US, and we're learning as we go. We're getting a lot of great feedback. I think we're fortunate in that I have this background as a, as a product person, emailing customers every day saying, 'I want to hear your thoughts. Please share with me what you need. That'll help inform our priorities as we move forward.' And, and attorneys are surprisingly vocal about this. It's, it's been a nice surprise that attorneys are willing to invest time to give us, to give us their thoughts so that we can leverage those.
The next 18 months for us is really going to be about go-to-market, starting to build steam. We're building brand awareness all over the place. We've got, we've got articles about us in the American Bar Association, Forbes, podcasts like this. It is a grassroots effort to, you know, get ourselves out there to the half a million or so law firms that are in our target.
Jake Aaron Villarreal: Really cool. Well, I'm excited to see where things go for you, Hans. If anyone wants to find Deliberately AI, where do they go?
Hans Guntren: Yeah, our website's uh perfect and it's that, it's just deliberately.ai. Lots of information there about our product and if people like, they can sign up for a free trial. Only takes about two minutes. We'd love to, to have them.
Jake Aaron Villarreal: Very cool. Well, Hans, I want to thank you for joining today and for the listeners for listening. It means the world to me. I'm your host Jake Aaron Villarreal signing off for now, but can't wait to catch up with you all on the next episode. Until then, Hans the world. Take care. If you like what we're doing, don't forget to subscribe, leave a review on Apple Podcasts or wherever you listen and follow us on YouTube where we go behind the scenes to learn what it takes to be a startup founder.
.jpg)
.webp)
.webp)
.webp)
.webp)
