15 years ago, Preston Clark built Law Insider, one of the largest public contract clause databases used by lawyers — whether they admitted to it or not.
He later founded SimpleDocs, a legal AI startup taking a very different path from its rivals: staying bootstrapped and transparent on pricing.
00:00Simple Docs is being compared right now in the market to Ivo and GCAI. Where do you think you differ from these two players? So, first Simple Docs sometimes feels too simple compared to the other vendors who have raised huge amounts of funding.
Speaker change: Insinuated in your question, simplicity is code for less.
Speaker change: One thing I've noticed about these legal intelligence platforms targeting enterprise clients is that the pricing is never transparent.
Speaker change: Hiding the price is the best way to maximize the average deal size. Contract
00:31review software. There's no reason that this shouldn't be transparently priced. If if anyone is watching this and is paying dollars per user per month, you're probably paying too much.
Speaker change: And if your kids were to start their careers today, would you encourage them to still go to law school and be a practicing lawyer?
Speaker change: I think I'm supposed to tread lightly on that question, but I don't feel compelled to. Welcome to another founder interview for a legal intelligence platform D types. Today, I am speaking to Preston Clark, the founder and CEO of Simple Docs. In this conversation, we will get into the origin story for
01:01LawInsider and how it led to Simple Docs. We'll talk about their product philosophy around simplicity and whether that is a deliberate advantage or a gap they're trying to close. I'll also ask Preston some tough questions around how he thinks a bootstrapped company like Simple Docs can compete with the other very well-funded players in such a fast-moving legal AI market. What he thinks of his competitors and also what is the reasonable pricing for AI contract review software. Let's get into it.
Speaker change: Before I knew you, Preston, as the founder of Simple Docs, I knew you as
01:33the founder of LawInsider. I am genuinely very curious the relationship between LawInsider and Simple Docs and how the two companies evolved over time and now is actually one company.
Speaker change: time ago, we set out to organize the world's contracts and that was the thesis for LawInsider. Parsing and organizing and structuring that data as it over time, it just became this passion project that along the way very fortuitously built a massive community. We sort of appeared anytime anyone was on Google looking for a contract or a clause or something more nuanced, they
02:04would find their way to LawInsider. And so, it became a massive community, a massive audience. But we knew we had something and and so we experimented, we tested, we tried to find different products to monetize and we tested just about everything and nothing stuck. At least not to the scale I needed it to. And then the AI wave happened and it was this perfect moment where all of a sudden what our audience was asking for were AI tools that sat on top of and referenced the LawInsider data set which they had come to trust over many, many years and they wanted
02:34that same capability but with AI. So, they didn't just want to come in and and copy a clause and leave, they wanted the AI to draft for them, to review for them, but always in a way that was referencing back to and leveraging this data set that they had come to trust. And so we built Simple Docs with that in mind, with the idea of it being an enterprise software layer that sat on top of the LawInsider data set that leveraged AI and that's that's how we got here and it took longer than I wish it had. And as a result, Simple Docs is scaling quickly in large part because of that foundation.
Speaker change: So many questions there, Preston. But
03:04before we dive into Simple Docs, which we will get into, can you walk me back into when you first started, is it because you just were so passionate about contracts that you were like, I need to put together this database?
Speaker change: transactional lawyer technically, sort of by by training. I was an in-house attorney, but I'm truly a salesperson and so I look for revenue opportunities. And so I don't want to represent that this was all altruistic and it was just sort of surfacing the data to the world and and sort of going to bed well at night knowing that we had done that. It
03:34was always there needed to be a commercialized model. But to answer your question more directly, we saw an opportunity to build a resource that would be highly engaging for global transactional attorneys. I knew that at the core to be true cuz I had been one myself and I knew how much you relied on templates and historical precedent internally and then some cases from old law school friends and others to do your transactional work and to to make this much more accessible than it was before. It was a website called 1cle.com, Rocket
04:05Lawyer, LegalZoom were trying to do it to some extent, but it felt to me that there was an opportunity if we just obsessed over it long enough and I think that's maybe the unique element because we were going to privately fund it. We weren't going to take outside capital. We weren't going to immediately sort of represent a clear thesis and path to a billion dollars. We were just going to say, this is a valuable data set. If we can if we can segment it and structure it in a really logical and intuitive way and then if Google looks kindly upon us, which they did and have, we knew that we would have something of value. So, I didn't think there was a commercial
04:35aspect, but it was a very patient one because we sort of knew if we build it, they would come and if they came, a business would emerge out of it. Did I think it would take, you know, a decade and a half? I did not. But nevertheless, here we are.
Speaker change: I want to share like a personal story as well with you. When I first returned in-house after building my first business, I transacted a lot with LawInsider. And at the time, I remember the more senior counsel would find that, I mean, on the surface they would say a scoff and tell me, "No, I never use LawInsider. I always cuz the clauses are
05:05always stored in my head." Until one day, I got a markup draft from the senior counsel and it had a hyperlink from LawInsider in the contract. So, that's how I knew that she was also referencing LawInsider clauses and you guys embedded that hyperlink into provision that she copy and pasted.
Speaker change: That's incredible. LawInsider is not something that was celebrated or that most lawyers went to the mountaintops to stream.
Speaker change: I started seeing a lot of first batch of legal AI companies emerge. And at the
05:35time, I even remember approaching the legal tech department of my company to tell them that, "Hey, I want to recommend two great platforms to you. The first is LawInsider. It's great because you have all of the contract database there, all the clauses. But I want you to also pay attention to the legal companies. At the time, it was like Robin, it was Harvey that was just emerging. I was like, "They're even more powerful than LawInsider because they take all those clauses and they generate your customized clauses for you." So, at that time, I always wondered why LawInsider didn't immediately jump on
06:06the AI train. And I followed very closely. I saw the partnership with Term Scouters and that's how I actually knew about Term Scouters. And I just wonder, why did it take so long? Is it too late or am I missing something here and you're entering the market at just the right time?
Speaker change: Great. So, it's a good question. It's one I think about all the time. More companies die because they're too early than too late. If the market is big enough, if the category is big enough, it's really hard to be too late, I think. Like I can imagine, like you've seen it. Like there's been startups that have come out of nowhere in the last 6
06:36to 12 months that have emerged even since we got here. But I think you made a point earlier which is, you know, what took us so long and and shouldn't we have moved faster? And yeah, we probably should have. But the reality is the market is huge and we're growing fast. And I also think we got to learn a massive amount from the market and from our competitors that gives us a really strong advantage now. You'll appreciate this as a legal AI nerd like me, I do these plot lines of our major competitors. So, we sort of go up against three or four competitors regularly and I look at when they hit product market fit, how many employees
07:06they had, when they did their first and second and third funding rounds, how many employees they had at those different trajectories, how many customers they reported having. And I do that just to sort of benchmark us in terms of our growth. And I will tell you, I'm exceedingly happy with where we are and how we're keeping pace with with this market. And that's even just on, you know, all things being equal. All things considered, I'm really happy because we've been able to do this at a fraction of the outside capital and that's really exciting. The other piece though that is perhaps the most important answer to this question is, what is our goal? Where are we heading,
07:36right? Cuz for you to sort of say, were we too late? Well, it's too late to do what? To win the entire market? To win a portion of the market? Well, for us, our ideal customer profile is global, multinational, large corporate in-house teams specifically. It's not solos, it's not law firms, not mid-size law firms. It's not SMBs, it's the enterprise. And our ICP is about 20,000 we estimate, 20,000 companies and we need about 5% of that or 1,000 for us to reach our goals. And what does that mean? What does it mean to have a thousand enterprise
08:07customers? It means to serve them very well. It means to build for them. It means to listen to their needs. It means to make sure that we're training them and doing all the things that they expect from an enterprise vendor. But to do that, I'm definitively not too late. If if I'm Harvey, like I don't know if another Harvey can emerge right now and sort of break into the Harvey-LegalZoom duopoly for big law, I think that that's probably too late. But for what we're doing, I think we're right on time. Yeah. That the companies or the startups that come after you are still on time or do you think they are too late?
Speaker change: Oh, no. I don't think they're too late. I think more can emerge. I think more
08:38will emerge. No, I don't think it's too late. I wish it was too late. Right? I wish the door had closed right behind me and then the last one, but I don't think that that's true.
Speaker change: How do you think that can translate into helping legal teams come understand what's going on in the market right now with all of these different vendors? And what kind of proxy metrics or signals they should be paying attention to to discern whether a vendor is a good fit for them or not? Yeah. I mean, I answer that question in two ways, but before I give either of those answers, I will say I think that the work that you are doing from a
09:08benchmarking perspective is very, very necessary and important to help distill this in an unbiased way cuz I have a bias to my software, to my team. I think we're unique. I think that we are wonderful partners. But I think at scale and as more even more vendors emerge, having some rigor around that evaluation framework will create some calm in a market that doesn't have very much calm right now. But let me sort of break down the answer. So, I think one of the answers is a non-answer which is, at this exact moment in time, this is we're in new category land. One other time in
09:39my career did I have the good fortune to be at the beginning of a new category and there's a couple of years of market chaos, of first vendor adoption where advanced evaluation frameworks just unnecessary for most buyers. I shouldn't say unnecessary, they're unused. They may in fact end up being very necessary, but but the the buyer is just proceeding without it. They sort of they they are with five, they narrow it to The other time I saw it was tight very obscure. It was a new Title IX mandate for US colleges and universities went into
10:10effect in like 2014-2013 time period and suddenly like 1,600 to 2,000 colleges and universities basically overnight needed to find a compliance training solution for their entire student body for their entire workforce. And we happen to be at the time right at the we were the perfect vendor at the perfect time to do that. And so we got to watch that unfold and it was like a 2 and 1/2 3-year journey of of new vendor adoption. And at the end of that the rigor was was instituted thereafter. So it was like 3 years of
10:40just like buy buy buy buy and then it was frameworks for evaluation thereafter so that when you would go to your second vendor you would use a level of rigor that you may have bypassed. It doesn't mean that they just sort of bought saw saw unseen. It was that the statistication of the evaluation just took some time. It took some battle scars unfortunately for for me. And so I got to see that play out. I suspect that that's going to play out here to bring it back. And my expectation is that it's going to be some failed implementations. It's going to be some disgruntled customers. And it's going to be some
11:10happy customers that help you know with leaders like you shape this evaluation process. Part two of my answer to you is that AI is making software easy to build, faster to build. Basically any feature that one of our competitors launches or that we launch can be mirrored relatively quickly unless it's grounded in something proprietary of which there is not much of out there. And so now the question is how do you select a partner um or a vendor when the checkboxes of features is 95% the same
11:43or 100% the same. And I think that irrespective of what your feature list indicates it is how do those features match to the uniqueness of our organization, to our approval flows, and to our hierarchy, and to our policies. And I think that the better you can match that the the more trust is built. And I think that this is the concept of partnership and trust become resounding. We don't take outside capital. One way one sort of proxy for that I do think is VC funding. I think it's a false proxy candidly because most of the venture capital goes into sales and marketing and so I don't actually think it's
12:13indicative of how the product is going to improve. I'm glad you're here doing the work you're doing, but I think that the dial is going to turn up even more as vendors fail or as implementations fail. And now next time you just you go in with a level of rigor that perhaps you didn't before. Yeah, that's definitely the sentiment that I've been hearing from the early adopters. As a renewal comes up In fact one of the interesting stats that we have is more than 80% of the legal teams that have procured a legal AI solution now are not happy and satisfied with their current with their current aware. And they're
12:43all actively exploring or considering other options, which is insane. Yeah, with the stickiness of the industry that's going to you know I'm sure the VCs are terrified. So speaking of the product of Simple Docs, I have heard some feedback from the market that Simple Docs sometimes feels too simple compared to the other vendors who have raised huge amounts of funding and built out a wide range of features. And at the same time I've heard from legal teams that they prefer Simple Docs precisely because of the simplicity and that simplicity makes it very easy to use and
13:13not overwhelming. So I wonder whether that is a deliberate product philosophy or is it just a constraint you're trying to overcome right now? Yeah. No, it's deliberate. So insinuated as you should have in your question was a sub-question which is is a lack of outside funding resulting in narrower product surface area such that simplicity is code for less. And I actually think we win. I know you're getting a chance to speak with some of our customers. We win because of our breadth which is ironic
13:43because we are obsessed about simplicity. So let me just unpack that really quickly. We have multiple products that serve different use cases in the realm or category of contract automation. And do this as I mentioned exclusively for corporate in-house teams. In order to remain simple within those categories we have to do a lot of hard work very focused on the use cases that are most valuable to our customers. And we have a design philosophy which is if you add something you should subtract something. And anytime you create more
14:14complexity because you're adding a new feature or a new product or a new set of capabilities part of the requirement of the product organization is to figure out how that should be incorporated into the user experience such that it remains as simple if not more simple than it used to. And that is very hard to do. And it's hard to do in part just because like you know if you're you got to hide something that people love and where will it live now? And it's also hard because you want to sort of put your chest out and say look how much cool stuff we have. And we don't believe in
14:46that as a philosophy and that takes a lot of it creates a lot of requires excuse me a lot of discipline and a lot of fortitude and a lot of conviction that the things that you're building are the right things. Which brings me full circle back to being very ICP ideal customer profile focused. And so you will find when you speak to our enterprise customers they love the simplicity. Why do they love the simplicity so much? It's the exact features that they want and need. Why do they care about that so much? And this is maybe the important part is that we're not primarily a consumer experience tool. We're primarily an
15:17enterprise tool. But that means that when we do a POC and we win an account
18:06it's
Speaker change: a CRO and GM of a venture-backed business. I know those constraints. Those are not our constraints. We have what we call proprietary distribution. We own our distribution engine. We own lawsider.com. We own 1nda.org. We have a massive newsletter list. We add new subscribers every single day in the hundreds. This is a very powerful engine that affords us the ability to not invest in marketing at least not in the way that the competitors are. We don't have to be sponsoring any golfers as cool as that would be. So the transparency in pricing allows us to go
18:36through an evaluation cycle faster. It allows us to differentiate from our competitors instantly. Simple Docs is a simple product. It's easy to use. It's easy to buy. Like these are things that are our core principles or core values. But and up the part that I'm most like I'm passionate about all of that and I feel very strong in our position. But the part that surprises me is specifically contract review software. This is the category that's exploding. Everyone is buying this right now. And they have been for year and a half two years. There's no reason that this shouldn't be transparently priced. I
19:07understand that workflow automation for example we do this for some really big customers. There's customers that pay us $10,000 a year and there's customers that pay us $100,000 a year. It's both workflow, but their use cases vastly different. Vastly different scopes of investigation and complexity and that's reflected in the price which means if they come in and say how much is it? We have to say we will tell you but we have some questions first. But when we're talking about a per user per month or per user per year software tool that sits alongside Microsoft Word that is designed to contain playbooks and
19:37fallbacks and negotiation rules etc. There's no reason that you shouldn't have and be able to commit to a per user cost. Now there can be volume discounts and other aspects that that create more favorability for different customers, but I don't get it because this is very much a product that would lend itself to that type of transparent pricing, but at the same time I'm very glad that our competitors don't do it. I think that will change. Maybe it'll change later this year, maybe next year, but right now it's it's clearly getting
Speaker change: to give the legal teams that are currently shopping out there a useful benchmark reference price tag for a
20:08contract review software that sits as a word plug-in, what would you say is the range of reasonable pricing? Okay, it's Microsoft Word integrated, it's SOC 2 type 2 GDPR compliant, zero data retention, no one's training on your data. So it meets all of these criteria. It has custom playbooks, which means you can build your own. It has hopefully a library of playbooks, so if you don't have one, you can build off of or use what's there. It has a legal engineering team, has a support function. None of us went to law school to learn how to build AI playbooks. So it has as capability. It has single sign-on. Like you they go
20:39through this like core list of capabilities. And and maybe it integrates with outside data sources like LawInsider, like you sort of you go through this checklist. Maybe it integrates with the repositories, so it's giving you some precedent benchmarking. You go down the list, the more complete that feature set is what I just described, the higher the price point in the market goes. But the range today is 150 to 179 per user per month on the low end, all the way up to what I understand to be five $600 per user per month on the high. And that's a a pretty big delta, and I don't think that that
21:10delta is easy to justify because I don't think that if anyone is watching this and is paying $500 per user per month for a word add-in, I think you're probably paying too much unless there was a level of service and implementation where, you know, they work with your team for six months and implemented 37 playbooks. Like I there there may in fact be a defensibility there, but I don't think so. So I think that that's the range. But what would what would you say is the rough number of seats that would get this pricing? Yeah, so we have a we have three sort of this
21:40is I'm going to use us as an example, but I think it's probably consistent. So there's sort of three vectors. We have some minimums if you're going to do an enterprise evaluation process. You can go to LawInsider.com by the way and and buy like one seat with your credit card and like pay monthly. So we have a sort of no friction just buy now path, but majority of our customers are coming through an enterprise experience and they expect due diligence and trials and all these other things. And in that realm, there are seat minimums. They're low, but for our basic package is three seats and for our pro package is five seats. And the two other vectors are for
22:10nonprofits and for government industries and in similar, we do pretty significant discounts just right out of the gate, 30 40% off for those categories. That that layer one. And then layer two is discounts start for us at 10 seats and above. Um and so we have customers that will come in and buy 15, we have customers will come in and buy 50, all the way up to to 100 plus. And each of those come with with an additional discount tier. And so in in plain terms, the range that you might expect is off of our list price, we'll go down as much
22:40as an additional 50% depending on volume and depending on industry. But we try to be very transparent in the in the buying process. We don't publish that level of detail because it's we don't want to create that sort of overwhelming complexity. List price price, and then we discount based on volume and based on industry as the numbers go up.
Speaker change: That's super helpful. Thank you for sharing that Preston. And usually being compared right now in the market to Evis and GCAI. And to I want to give you an opportunity just to share with the legal teams are currently
23:11considering the three right now, where do you think you differ from these two players and is the choice ultimately coming down to what you mentioned before, betting on the founding team. So which founder they like the most because the features and the products are similar in many many ways. So first, massive respect for Cilia, for Men, for what they're both building. I think they have beautiful brands. I think they have great products. We lose to them all the time and we beat them all the time. And listen, if you ask me why I own the car that I do, a lot of it is emotional.
23:41Like I own a Defender because I wanted a Defender when I was 15 because I wanted to be in the safari in Africa and I wanted to just drive around all day by Robert Redford. So like there's an emotional aspect to anything we purchase, and I do think that in particular, Evis and GCAI have wonderful enterprise brands. And I think those brands are emblematic and are reflective of their CEOs, and I hold them both in incredibly high regard. Nevertheless, I compete with them every day. I am ruthless and I want to beat them every single day. In the case of Evis, I think
24:11that our differentiation is on level of service from a legal engineering perspective. Electra Pona is is unique and singular in her ability to engage our customers and the market from legal operations perspective and from a playbook development perspective. And I think that as good as they may be on that as well, they're not as they don't have the reputation we have in that regard. The benefit of sitting on top of the LawInsider data set to give market standards, to give benchmark, we have a decade and a half of reputation built around that data set. They don't have that. They can pull in from other data
24:41sources and I know that they do, but they they're not sitting on top of something that is proprietary in that way. Do think candidly we're about 40% less expensive than they are for a product that is basically the same from a feature perspective. I think the application is very different, so I think we are more simple from a user experience perspective. And certainly they have massive customers and we have massive customers. I think that we have been doing this at a better level internationally. I think that they've done a really good job in California, but I think if you look at our roster of customers, I think we've done a better
25:11job of capturing those use cases, multi-language dynamics, really hierarchical complex approval flows for distributed legal in-house teams. I think that's where we've won. And then really quick on GCAI. I know that they've come out with a word add-in. I think it's they're they're still probably a few months behind, maybe more from from us in the in the market that has been at that a bit longer. I think that they similarly captured a lot of of hearts and minds of in-house legal teams in the Bay Area, similar to Evis, and I think they have struggled to go
25:41international in the way that we have. And so we tend to go head-to-head with them less often. We do have a chat-based experience like they do, but I think the in-house teams, the word add-in, the repository, the workflow, that combination that I mentioned, I think we're most similar to Evis. We're most different from GCAI. And so I think when we've done postmortems and and we've lost to GCAI, it was literally for reasons that were outside of our control. It was felt very non-ICP. It's me and one paralegal and we're not getting any more headcount. I have to do
26:11everything and I just need this browser experience as I need to draft and I need need to do these other things and I just need one tool to do that. Whereas for us, it's much more about the enterprise experience and access and how we're rolling things out to broad teams globally. Can you give maybe one or two reasons that you've lost in your pilots that you're like, "Dang it, we need to fix this ASAP." And what did you do about it? I think that to go back to the GCAI, we don't have a huge prompt library. We have other libraries. We have playbook libraries and other things, but I think GCAI has done a
26:41really good job of creating these these libraries and catalogs of prompts that that I think feel very actionable and very pragmatic for GCs that are like, "I don't know what to do. I don't know how to use this. Like just give me questions to ask."
Speaker change: Doesn't have to be these two competitors unless that's all you go up against, which I I assume that's definitely not the case. That's not true. That's not Those are the two big ones for sure. So there's something that we internally call the Christmas tree effect, and it's when playbooks are applied or AI-generated redlines are applied and they're applied in a way that does not feel human in nature. And so it can be
27:11factual and or accurate in terms of defending the rule that you set out to defend, but the the feel of it feels off. And this was surfaced, actually you'll appreciate this, this is interesting, by our early ALSP customers. They would come and say, "Preston, I can't send this to my client because it doesn't look like me enough and then they may not give me credit for it and then my my pay will be docked." So it was very pragmatic. It was very much like, "This doesn't look good enough and so therefore I have to go in and fix it and by the time I'm done
27:41fixing it, I haven't saved any time." And this is this is something that we detected, you know, a year ago. And we've made massive improvements and the Christmas tree effect is largely gone, but there are times when the result, while accurate, doesn't look as good as it should, and it's that last mile of perfection that I think, you know, I suspect that all of our competitors struggle with that to some degree, but I think that that's one that I am insecure about because I want it to look and feel as good as if you had done it yourself, and that gap, while quickly closing, is not all the way closed yet. Yeah, that's super honest. I appreciate it so much,
28:12Preston. And I wonder, you're building in a space right now that is constantly pulled by all kinds of hype cycles in all different directions, and there are so many new tools emerging and also new capabilities emerging for general purpose models. How do you stay sane and decide on what to focus on and what to just block out?
Speaker change: Yeah. Um what is the expression, strong opinions loosely held? So it's my job to help prioritize what we focus on as the CEO of the business, what we say no to. I say no more than I say yes because we we
28:43have an abundance of ideas and the markets we can pursue and products and features we can build. On one hand, your brain has to just be open to the chaos of this unique opportunity to try to find things that you can bring back to the mothership and bring into your building and into your go-to-market. But the real answer is that it has nothing to do with my experience in legal tech or my experience as a lawyer. It has everything to do with my experience building in enterprise software companies, which I've been doing for over a decade. And if you are serving the enterprise and if you have a
29:13relatively narrow ICP, then it's fun and important to look at the outside and to be to watch what Legal Week is doing or to go to Legal Week and and, you know, see everything that's going on. And gosh, we have an iPhone app. Gosh, do lawyers actually want to draft via their phone? They just want to speak to like we have to leave space for all of these these wild and and cool ideas, but my real job is to just talk to our customers. And it has to be the right customers. It has to be the big customers. It has to be the smart customers. And they guide the way if you
29:44allow them to, right? Which means you have to be a disciplined we're not building everything that they ever wish for, but for me, it's so much more about that and bring this full circle back to what it means for us to be a privately funded business and not have the pressure of outside capital, which requires us to grow into some obscene valuation, which by the way, invariably means we pursue more markets and more opportunities than we can manage or even sort of intellectually figure out how to how to pursue. But I can say, Anna, we're hyper-focused on a very specific ICP for which we need to capture 5% of
30:16the market share in order to win, in my opinion, and we build the things that they need. I'll end on a story, I'll keep it short, but we have a partner in South America that is a cell tower company, and they have thousands and thousands of active contracts between telecom companies and regional and government agencies or bodies that own the mountains or volcanoes upon which the towers sit. And the data inside these contracts has vast variability and vastly critical information relative to the billing obligations, what triggers
30:47different cost structures or increases or decreases, and these negotiations evolve over time with amendments and other things, and sometimes those amendments are in emails and sometimes they're formalized in documents and sometimes they're in PDFs, and like all of these different things. And there's now this team, or has been, of lawyers that have to painstakingly go through these contracts over and over and over again to try to defend their position relative to these thousands of partners that they have. And by the way, it's English and it's Spanish and it's Portuguese and it's That's it's all of this
31:17So you find these use cases like this, and then you have a partner like us who comes in and we go build for it, right? We design a system of evaluation and review that mirrors the work that's happening manually. But I think you can only get there by having deep conversations either yourself first as a legal department or with a partner like us to help evaluate where those opportunities are. That makes a lot of sense, but I kind of want to circle back to end our conversation on a human note, which is what all translate into for the
31:48human lawyers, because once a lot of this work is automated by machines and by artificial intelligence, where does that leave us, the humans, in the future? And I guess another way of asking this question is, would you, Preston, if your kids were to start their careers today, would you encourage them to still go to law school and be a practicing lawyer? Yeah. No, I wouldn't. I think I'm supposed to tread lightly on that question, but I don't feel compelled to. I think that if something is inherently inefficient and technology is here to make it efficient, and I am
32:18in the business of building and selling that software, then I have to be fully committed to the ultimate outcome. And in the moment, there's an undercurrent, because if I go into a legal department, as I do every single day, and they see the power of the tool, invariably it's either said out loud or you feel it in the room that there's things happening with this tool that make some aspects of the work of the job obsolete. And in so doing, headcount will be altered either in the short term or the middle term, and that is real. The less sort of dramatic version of this for the legal
32:48community is we all got to watch as Uber, many years ago, was valued on the promise of autonomous driving, which meant that all of the drivers that had built their livelihoods on driving taxis, black cars, Ubers, would suddenly be out of a job, and Uber at one in the same time would be fully committed to serving the driver community. I'm glad we're selling into in-house. I think it's a much more complicated conversation to to to have reality for law firms, but for in-house teams, efficiency matters, outcomes matter, and if you can do it for less headcount,
33:18that's cost efficiency, and I think that that's a win, and I don't think we shy away from that.
Speaker change: Thank you for giving me your honest take throughout the entire conversation. I really, really enjoyed it, but I do want to end on a high note.
Speaker change: [laughter]
Speaker change: Not on the end of the profession, though. Good. The thing is, we we don't know, right? There there will lot of new careers and new jobs emerging like the there's that we just cannot foresee at the moment, but for sure, and I agree with you that some of the traditional roles and or parts of the traditional legal profession is going to be automated and made and be replaced by
33:49AI, and I think that's a sobering truth we all must accept at this point, 3 4 years in. But
Speaker change: I also wouldn't have told my kids to go to law school 10 years ago, either.
Speaker change: Okay, coming back to my last question to you, which is super curious, and I ask every founder this, what does your tech stack look like today? And this could be like what kind of AI tools you use or other cool technology that you're using to build your legal AI empire. I think you would need to go to each corner of the business to look at what we're doing.
34:19But I'll tell you, myself individually, I am a gathered I am a sales-focused we're a sales-led organization. We are enterprise sales company, I'm much more of Dale Gove Steve Ballmer than I am Bill Gates. I'm not smart enough to to be a visionary in that way, but I'm pretty good at building businesses, and so the tools that I use reflect that focus. And so things that I care about are synthesizing large sets of information. We use Otter, for example, for sales call recordings, we spend a
34:50ton of time going through those recordings. We layer that in with Loom videos, we do lots of sales training by using Loom and the analysis of Loom. This is not interesting in as cool as I'm sure some of the other founders have told you, but we love the new version of Typeform, the the survey tool, it's really I've been building surveys and survey instruments for a long time, and one of the hardest parts is actually not you know what questions to ask, but actually instrumenting it into a survey has been really difficult, and AI has accelerated that, so you can just take, you know, 100 questions and it actually will do a
35:21pretty good job. We use it for customer and user surveys, so when we do monthly active usage reports, we'll then dive a layer deeper and say, you know, how how often do they use it, how would they feel if they lost access to this product. We do sort of that product market fit survey analysis as well as NPS. So I think it's for me, it's it's all about customer experience, the buyer experience, the sales experience, and the tools that I focus the most on are the ones that give me the deepest insight into that. You So like literally right now I have I have my ChatGPT up. So in preparation for the interview, I thought about the questions you might ask. And so there's things like that
35:52that I've done that that relate to sort of everyday use of AI like like GPT and Claude. Well, thank you so much, Preston, for this conversation. It was a wonderful chat, and hope we get to catch up soon. Thank you, Anna, really appreciate it.
