E52 - Is Legal AI a Trillion-Dollar Opportunity? Legora CEO, Max Junestrand

An episode 50, I interviewed Harvey Founder Winston Weinberg, but I specifically waited until episode 52 to interview Ligora's CEO, Max Yunstrund. Hey there, I'm Zach Abramowitz and I am illegally disrupted. This is episode 52 of Zach Abramowitz is legally disrupted, but first, here's my hot, disruptive legal take. Now in 2023, shortly after the launch of Chad Gbt, all anyone wanted to talk about wasn't Harvey or Ligora, it was actually co-counsel. The 10-year-old YC startup originally called Case Text that had gotten its hands on LLMs before just about anybody else and they had figured out how to wire these models into legal workflows. It's hard to believe it now, but the conversation around Thomson Reuters acquisition was, how could they possibly justify paying 650 million dollars for this company? Their institutional investors were asking that question the very next day after they announced the deal, but by the end of 2023, that price didn't sound nearly as crazy anymore because Harvey had reached a valuation of more than 700 million by its series B offering led by Clan or Perkins and a lot of Gill. And for most of 2024, the question I began to get was Harvey or co-counsel. Meanwhile, in early 2024, YC funded another legal A startup called Leia, which would eventually rebrand as Ligora and position itself as Harvey's primary competitor. That positioning has paid off. Co-counsel began to fade from the center of the conversation. And for many firms whose attorneys were asking, "Hey, why don't we have Harvey?" But the firm maybe had a bad experience with Harvey sales team or they had felt left out of the somewhat stealthy go-to-market, Ligora now emerged as a compelling alternative. While Ligora has been playing from behind, its catch-up game has been remarkable. By the beginning of 2026, the legal AI ecosystem was no longer all about Harvey. The conversation had definitely shifted to Harvey versus Ligora. So, why did I then specifically separate these two interviews? And in fact, in episode 51, we had Will Chen from my co-sss, who has been one of the most vocal outspoken critics of Harvey and Ligora. Well, I think a bit too much has been made of Harvey versus Ligora. Earlier this year as an example, Harry Stebings featured Winston and Max in back-to-back episodes of 20 VC, really amplifying the Harvey V. Ligora Coca-Cola versus Pepsi narrative. And at a high level, I get it, but legally disrupted isn't only about covering the high level. Harry is covering Silicon Valley and startups in general. I'm covering the impact of AI on the legal ecosystem. And from my perspective, Harvey and Ligora are two different companies led by founders with different visions. And while many people tend to see them as essentially the same company, the same product, I think these differences are going to become more apparent over time. In both episode 50 and 52, I went deep with each founder to give you the viewer a better understanding of these companies on their own terms, not just in comparison to one another. Because ultimately, if you as a lawyer or a law firm decision-maker are choosing one of these companies as your transformation partner, you should be diligently seeing the founders' vision and their ability to execute just as much as the product itself. So, without further ado, let's go deep with Max. Let's learn more about his vision for Ligora and the legal profession. Let's get disrupted. So Max, I feel like part of Ligora's magic has been your ability to meet users and lawyers where they are. So, we are recording this on May the 29th. And it seems like where the entire legal industry is today is obsessing about this press release that came out yesterday from Kirkland and Alice talking about how they're building their own new solution. And certainly all the lawyers on X and LinkedIn and social are having a whole time with this. I know it's like fresh. I also know that you're pretty connected over even at Kirkland. So, despite the fact that you might not have been mentioned in this press release, what's your reaction to the news? And how do you think, what's the important context? I think that the really large clients and enterprises are starting, you know, we're a couple of years into the AI journey now. And they're starting to ask quite fundamental questions around how and where are these firms really applying and not just augmenting the way that they used to do things, but actually reinventing parts of their services. And different firms are on different, you know, trajectories on that journey, right? Like, you have the sort of the bell curve. And I think if you're Kirkland and you're number one by a lot of metrics, you really need to show a lot of strength and a lot of power to those clients to say, we're taking this seriously. Now, I don't think the entire equation is, you know, spending hundreds of millions of dollars on building your own thing to show that you're serious, but I think it's a good part of the equation. And they're using a muscle that's not every firm has, right? And so, 100 million is a rounding error for Kirkland. This could be a total screw up and it wouldn't impact them at all. And so, you know, they can go out and market and orchard while everybody else is marketing apples. And that's very appealing. And so I think they're doing a really smart move of leveraging, yeah, part of their weight in a way that nobody else can. And we'll see what comes out of it. It's certainly a good headline, but you know, at this point, a couple of years into into the legal AI, you know, sphere that we're in, I think press releases are one thing, results are another. And I'm very excited to see the results. One of the things that's interesting about your company and your product, I mean, forget the crazy growth which we'll get to, is you were initially designed for law firms. I know you're also selling in to corporate legal and that's certainly like an area of emphasis right now. And you know, you guys are showing up at all the major legal conferences for in-house legal and a corporate legal and in-house legal teams are so drastically different in many ways than law firms. And very often what I'll hear from people who are in-houses when I came here from the law firm, this is so different and in many ways I wasn't necessarily prepared. How do you design a product that has to be number one for law firms and number one for legal departments? That's a great question. And I think zooming out a little bit, the the litigation department of a really large corporate is actually more similar to the litigation department or practice in a law firm than it is in the M&A practice at a firm and the litigation practice at a firm. So already from the beginning because we went quite horizontal and wide within our initial target group, we had to serve M&A, IP, bank and finance litigation and in-house use cases. And you know, I think what's going to happen is every time the models improve, they improve at almost every single task. And so for the first couple of years now, we've been in the business of building the tools, the scaffolding and the context layers required to put these models to work. And then they sort of a little bit out of the box can handle the differences between the practice areas. And I think the main challenge that sort of separates the two is most law firms don't really work with volume the same way an in-house team does. If you're a very large in-house team in insurance, you handle a lot of claims. That is structurally a different business than Kirkland's M&A business. This is very different. And what we've had to do is we've had to do it. It's like the difference between shooting free throws. So if the only skill is, hey, we just need to shoot free throws. So as many reps as you can get, it's the same thing kind of over and over again. As opposed to like, hey, we now have to strategize for an 82 game NBA season. Right? And that's exactly right. And I do think like the complexity of the work is simpler in handling mass claims versus the never seen before transaction or take a company public or bet the company litigation. As I think naturally, there's been the most applicability and sort of immediate return on investment in the lower parts of the value chain. But it's increasing. Right? And everybody can see the writing on the wall that the complexity of the tasks that AI can handle is becoming higher and higher every single day. And so if you extrapolate that, then you understand that even if you're a firm like Kirkland, you have to start your AI journey three years ago and you have to build. to that to that world. I think what we're juggling is the different incentives, so the incentives in an in-house team is, let's cut down costs, let's cut down time, time, let's bring as much work as we can in-house and it's as effective as possible. Now, many of the firms have realized that this is happening, right? And they are actively transforming their service model and their delivery model to meet this new world where frankly, agents can perform tasks. And we're a little bit of the opinion that if an agent can perform a task, it will perform that task. The only question is, where does it get transacted or where does that work get carried out? And to LaGora, that doesn't really matter. It can happen in the firm, it can happen in the in-house team, it can happen on the software. The important thing is that it gets carried out and that software is used to do it. And so I think we'll continue to see the world twirling going forward, but it really comes down to the incentives that the in-house teams set out for their firms. - So there's so much to unpack here, but let's start with the point about your belief that the task needs to get done. It's not specifically important like who the party is. One of the things that when I've spoken with clients, when we show them sort of different levels of a transformative impact, one of the ways that we measured that, one of the questions that we would ask and sort of score this is, does it change who owns the process? Meaning if this was done before by a law firm and now it's done by a law firm but done maybe more efficiently. Yeah, that's impactful, but it's much more impactful. Okay, this used to be something that was done by the law firm, but now because AI or because agents, what have you, it's now done by an in-house legal team or it's done by a provider in Manila or whoever it is, that's already much more impactful. Are you seeing that already? Yeah, but I think a third option or maybe a fourth option there is just the law firm enable that new service in a very different AI forward way where actually the human involvement is very low, right? 'Cause there is an option where you say, okay, a law firm who service 50 in large banks as clients. They have economies of scale in solving, let's say different compliance use cases at scale because they can bring that use case to 15 clients. Whereas innovating within the bank, they're just solving it for themselves. And so I actually think that many of the law firms have an opportunity now to scale the or productize, really, their offerings and then take them to the market at scale. And the real question there becomes kind of a market share game, right? How quickly could you as a service provider take something to market, get scale on it, get many clients on it and then start to iterate? Because when you productize things, you need to have a quick iteration cycle or you're iterating with the clients. I think that's when one of the sources strength is for LaGuara, but that will then allow them to build a bigger and bigger mode around that service. One of the things that you said before was talking about the journey and how law firms and really anyone for that matter start in one place, but you're somewhere else three years later. So I've discussed this many times and said, listen, if it's just about turning on a switch, then you could theoretically be late to the game. But the compounding impact of early adoption is the AI brain is beginning to sort of instill this AI mindset such that you know better where and how to use the products. And you're also able to sort of now forecast where things are going. And you're able to start in some ways changing or maturing how you work with these tools. So my question for you is this obviously presents a big challenge for you. Because on the one hand, you as a company are farther ahead, both because you started earlier than most law firms thinking about AI seriously, but also because I imagine that you've got deep ties with all the AI labs. Your team, you've got-- you're working with top engineers. So you guys are like probably six, 12, or maybe even 18 months ahead in terms of what you know. But many of your lawyers, your customers, are in, let's say, maybe where you were in late 2024 in terms of how they're using the tools. How do you do that? How do you build for the customer where they are today but also knowing where things are going from here? Well, I think one thing that I've been for positively, surprise by is that I actually think many of our clients are much further ahead than what you may give them credit for. Further ahead. I actually think so. And I think it's because the light bulb moment has happened for enough influential companies and partners frankly, where it's like, wow, OK. It's here. It's transformational. We need to get going. And part of our job is to help them get us as far ahead as possible. I like to say that every firm that's on the Gora, every company that's on the Gora, should be in the top quartile of AI users, adopters, and suppliers in the way that they change their processes. And what we try to do is we, of course, talked to all the labs. We drilled that down into what will this mean for LaGora and what will this mean for the legal industry. And then we packaged that and we give that to our firms and to our companies. So I run a lot of roadmap sessions where truthfully, I have no idea what the world looks like 18 months from now. But thank you for giving me credit for maybe thinking that far. But I think we have a very good idea, sort of within 6 to 12. And frankly, it's also been very compressed because of what happened over Christmas with Opus. And Opus 4.5, 4.6, and now GPD 5.5. And the increasing capability of those models was so large. It was almost like moving from a pre-charty to a post-charty-pity world where just so many of the fundamental problems around tool calling, sequencing, long horizon tasks were solved with these newer generational models that it accelerated, which was already moving fast. And I think the really difficult part, as anyone in a company responsible for change management or responsible for innovating in the legal team, is it's happening 100 times faster than any previous technology wave. And everybody is prepared. Everyone is unprepared. And you wake up every week. And you're like, oh my god, there's just a flurry of new things. And I haven't even gotten started on a thing that happened three months ago. And it's just-- I think people thought we were going to work less because of AI. I'm certainly not feeling that. I don't think anyone in Mark's part is feeling bad. We're all working hand times harder. And you also sometimes feel like you're building sandcastles, because you just know that something new is going to come three months from now. And it's going to crash over your sandcastling. You have to start over. I say this all the time to lawyers. I was like, listen, I've got good news and bad news for you. Good news is AI is not going to take your job. But the bad news is AI is not going to take your job. You might be busier. I asked a room of lawyers this a couple of weeks ago at a partner retreat. I said, raise your hand if you feel less busy since AI emerged. No hands. It's very hard to predict. By the way, I like to flex on certain predictions that I've made and been right about. But I'm also like, I was deep into chat GPD. So deep in that at some point I decided late last year, you know what? I don't really think I need my Anthropic account. I'm just not using Claude at all. So like, this-- and I feel like I've been directionally accurate on a lot of things when it comes to AI and large language models. And even I had to go through that period of feeling deeply behind and then kind of eventually caving going back with my tail between my legs to Claude and then being like, oh my gosh, this is amazing. And now, shortly after chat, GPD is releasing many of these features and moving in that direction as well. So as we're talking about the frontier models, I have to ask them, sure, like you've getting these questions all the time. Are law firms legal teams, are they asking you, hey, why shouldn't we just be building all of this in Claude or maybe the answer, maybe the question will turn into Groc at some point. How are you helping them think through that and justify working with LaGora as opposed to working directly with one of the models? - Yeah. - Well, so we certainly got the question. And I think that's part of the credit of the very noisy marketing machine that anthropic is. And whenever they do a press release, the world goes completely crazy and sells off 20% of the public legal tech stock. And it was actually funny, it's like a bit of inside baseball, but we were raising our series D, asked that announcement came out. And then every investor that we were talking with was, oh my god, tell us about Claude for legal. And we just turned around the computer and we showed them the three markdown files that could, I think it was like three-arge and NDA, like generated a playbook and it would give out this. - And NDA really? Like wow. - Wow, and it gives us this table with a green amber type of thing. And then you could copy paste that over to word. And then you're like, okay, please implement this. So here's what I think of it. I think it's very good that the world is like waking up to the fact that these foundation models are very applicable in law. Even if we're out there screaming it from the rooftops, it's very helpful when a big microphone like anthropic comes and tells the world about this. I think engineering has had its moment. Now legal is having its moment, right? The foundational models themselves and the harness of let's say cloud co-work, however, is quite thin and then quite shallow. And for any like serious worker, if you try to put in an entire data room into cloud co-work and you go, okay, read through every document here. Here's my, hello, I use the guidelines. Here's the report I want you to fill in. It's gonna fail. Why does it fail? It fails because the harness, which is effectively the environment that you put them all in and the tools and the way that you allow it to reason, is it's built for everyone. So at the end of the day, it's like built for general office work and built for no one. And we have the luxury of obsessing over building one type of harness, our type of tools, our type of integrations, our type of governance and security checks so that no no documents get shared where they should and so that you have an audit trail of everything. And we get to obsess about that for one type of user. And that allows us to go much, much, much deeper than what the foundational models can because they have to play for every type of use case, reignically. And so I would really encourage everyone to try with tri-cloth and try GPT and try Gemini. And because the world is moving so fast, you need to try all of these technologies every quarter or every other month. - I'll tell you an anecdote from one of your competitors from wordsmith.ai and they're really focused on an house legal, but their CEO told me the story that he says when companies will come to him and ask about using his product, he'll say, well, do you have any internal chatbots? And if their answer is no, he says, go get one of those first because if you don't, you're not gonna wrap your head really around AI to begin with and our product's gonna be too sophisticated for you. And on the other hand, you're constantly gonna wonder, should we just have gone with one of the base products? He said, I want you to use it, wrap your head around AI and also figure out where this product comes up short and then come back to me and we'll talk. - Yeah, and I think that's exactly the right way to think about it. And as you start to really push at the frontier, like you know, we open the conversation about Kirkland, if you're a company that's gonna push the frontier or what's possible, that's what we wanna bring. And today, flavor of the month is Claude. Maybe a flavor of the month is open AI next month. And so it's important for us as well to have the relationship with all the foundation models and the labs to make sure that we can serve the latest in grades as through the product. And ultimately, I don't think that we are in the business of just selling a tool and saying, good luck, have fun. We are in the business of making every legal client as successful as possible. Now that means that software is a little bit like a garden. And every time the ground shakes, we have to like, replant the trees and we have to like, go cut the grass and we have to re-imagine what our software will be. I think, Zach, two years from now, you will have very, you will have sub 10% of our existing product still alive. I think 90% of everything we've built so far, I don't think we'll exist in legal two years or no. - So this is really interesting. And I don't know if you've ever seen, there's a fantastic South Park episode where the kids come up with this idea, this is back in like in the day of all the crowd sourcing the crowdfunding companies. And they said they were trying to build a crowdfunding company but the business model was, we're gonna sit on our ass, do nothing and make a lot of money. And this is the entire time they're talking about, this is like their business model. And I think there is sometimes this impression with tech companies that, oh, you just build it and then everyone uses it and the company sits around, does nothing and makes money. This could not be farther from the truth in the age of AI in particular, where it seems like one of the things that customers pay for, meaning if I'm a law firm and I'm going with LaGoura, the reason I'm going to do it is I'm gonna say, listen, it's great that we have this product right now but there's gonna be a massive change and I would rather outsource to a team of top engineers who have ties with the labs, that to me is gonna be the argument. They're gonna, because they're going to do that work every single time there's a massive change. They're going to come in. Is, does that feel, and I'm sure you're talking with other entrepreneurs, other VCs, does that feel like that's different in an age of AI much more so than it was like if you were building sales force? - Much, much. It's very different. And I think it's different because of a few things. One is the underlying rails upon which we are building are constantly being reshaped. And we're still learning so much about applying the technology in practice, right? And when you really see a private equity firm like leaning on what AI can mean for their companies and for their business, yeah. This is all like new territory. Nobody has really done that. And then you learn things in the field and you go, wow, okay, this thing doesn't really work. So let's take that back in a really quick feedback cycle, build it and get it out again. And I actually think a company's worth in today's age is more tied to the velocity of their, iteration cycle than it has ever been in the past because ultimately as you say, you're looking at the snapshot of today and the technology and the companies today. But you should probably pick a company and a partner to work with that has the fastest slope on their curve going forward. And pace of innovation, pace of innovation, right? And not to tutor our own horn, but I think that was like one of the big reasons why Legora came up from a very small legal market initially. We started in Sweden. Sweden is a smaller legal market than Kirkland. Right. (laughing) And now we scale enormously and I'm spending a lot of my time cycling the organization now. And thinking about how do we be a company that's going to be able to at scale serve our customers would maintain the velocity and the culture of and the pace of innovation. I think that is, how has your day to day changed since you started the company? Like what would you be doing on a typical Friday in 2024, 2025 versus what you're doing today? Well, so towards the end of, well, summer of 23, I was still coding. So there's a few commits from it. Dylan DeRipo, towards the end of 23, I was doing 15 minute demos and I was like back to back to back from 9 a.m. to like 9 p.m. every single day with demos because over the first summer after Chatepe T, I think a lot of people played with it and could see like, oh, it would help me write a speech, it would, give me a really good recipe. And people got to see it during their vacations. And then they came back in September. And we're like, okay, we're gonna see about how we can apply this technology in our company. And then they would go on the chat. The website, they would see that there's no European processing, none of the data is confidential. Like, okay, nobody can apply this. And then we were there to pick up a lot of that work. So I've moved from doing a majority of, I'd say customer work to maybe splitting my time between recruiting, recruiting and like, or building product and working with our top customers on what's next effectively. And I think the strength of a company like us now is that I am privileged to recruit and get leaders who have seen scale before, but are really hungry for the pace that we know. So David, our CFO, who just joined from Vanta, to great example, he built that company from 200 people to 1,300 people, 300 million in ARR. And now he's coming here. And he's just like, wow, like what we're doing in a quarter, you know, maybe you should take a year in the old sauce world. And say, now is a great example. So she just joined us from Atlassia, where she was the CMO. And you know, she used to have a 500 person team out of the Atlassia. This is like all the entire LaGoura org. And now the marketing team at LaGoura is 25 people. So our mutual friend, our mutual friend, John Levy, from Y Combinator, who's one of my, he and his wife are two of my favorite people in our space. And they're so humble and they've picked hands-selected some of the top legal AI companies, you know, in history at this point. Meaning, over the last, you know, really 20 years at this point in LaGoura included, he has a line that I just keep coming back to over and over again. As I asked him on stage, actually, this time last year, I said, you know, I see that you're investing even more in legal, is that because you care about the vertical, is this because you see LLMs is a great fit? And he said, no, he said, we don't care about verticals. The only thing we care about is talent. We are like, look at this as like the NBA draft. And we want to get the absolute top talented entrepreneurs. It just happens that the most talented people right now are want to build companies in the legal space. And I think you can see that not just with you, I think that I saw Scott Stevenson brought someone to Spellbook, very impressive tech exec into Spellbook right now. And you mentioned before that, you know, coding, AI coding had its moment. And now AI for legal is really having its moment. It seems like people want to get into this space from, you know, who've had really illustrious careers because they see the opportunity. So let me ask you a question. Do you think that LaGoura is a trillion dollar opportunity? Yes. Absolutely. I mean, we wake up. You know, it's fun because you're so in the arena. And every day you wake up and you think about, you know, what can I do today to move forward on our mission? And at the same time, you need to zoom out and go, okay, are we on the right directional path to that opportunity? I feel like I had enough people appreciate that you think this. And my sense is that I think Harvey and the folks over there probably think the same thing. And I think that there's this impression, maybe, that like you guys are trying to just like, you know, smoke and mirrors it until someone buys you for, you know, some amount of billions of dollars. And I've been saying recently, I'm like, no, I think that they believe it's a trillion dollar opportunity. So it's interesting to hear you say this. It's also, you know, it's like, I've set up the company in a way so that like, this is my life's work. And I decided that after we were invited to the, also inside baseball, we got invited to the, like most prestigious alumni event of YC four months after doing YC, which was very strange. We were the only company from our batch to get invited. And Brian Chapsky from Airbnb was the main keynote. And he went up and he was going to talk about the founding story of Airbnb. But then he went like, you know what? Like I said, this story 100,000 times. I'm just going to like fucking rant about what, like what I've done in the last like four years following COVID. And he described, you know, the feeling at Airbnb when they went from, you know, top of the world to COVID comes, they lose 80% of the market cap. And he, he was working with his executive, but the executive didn't really care about the company. They cared more about protecting their own reputation. And he just, you know, described this, this thing of, all right, like I have to decide now, is this my life's work? Am I going to like fight so hard one more time to like get this company out of the hole that it's in? And he, you know, described what, what Paul Graham would, would later write an essay on, which is like the founder mode thing. And I think like there's, there's good parts and there's bad parts of that. I think if you have a really well functioning executive, maybe you don't have to go founder mode on everything. And you have other people who can go founder mode on stuff on your behalf. But I came back from, from that alumni event going, huh, if he decided Airbnb is this life's work, I'm going to decide the war is my life's work. And that makes you think very differently. It makes you, you know, every fundraise we've done, I have fought really hard to maintain board control, which we still have in the founding team. And even though we've raised those, at this point, yeah. And it's like, I'm not going to let, you know, VC or private equity incentives guide this company, because I think I have a much better view of how it gets to a trillion than anyone else. But I think that's also just the number. Like I care about the impact that we have in the world. And then you, you can get a valuation as a function of that. Right. No, this is like Warren Buffett has the same advice when you, when you pick stocks, think about buying the stock and asking yourself, will this be the last stock that I ever purchase? And the one that I'm going to hold really for the rest of my life? And it does. It just, it completely changes your, your approach to that. No. Right now, you mentioned private equity before. I was joking on X the other day. I said, AI for M&A due diligence, boring AI use case or the most boring AI use case. Now, I know that this is one of the main use cases that everyone's focused on. But I look around and like, you know, M&A deals are still pretty pricey and you still hire lawyers for them. And in many cases, because of reps and warranties and insurance, the diligence doesn't have the kind of importance that it might have had even, you know, 10, 15 years ago when I was practicing. It does make sure it away. Yeah. So, but it feels like we kind of got like very focused on here. And by the way, I remember one of your team showing me a demo of the M&A due diligence product and I was like, wow, this is, this is absolutely amazing. But is that like, what is the impact right now and from your perspective of AI tools on M&A deals? And how are you seeing the best firms adapt? Is there a repricing mechanism? Is there a rethinking of the work? How are people beginning to grapple with that? So I assume you saw it, you know, pre the the agent to go as and pre the new agent because the new agent just to like touch on that quickly. Yeah. Because before we had all these different modules and you had to be kind of a super user to know when to use which module and how to tie it all together to build an M2M workflow. The agent basically what we've done is everything a human can do in LaGuara. The agent can now do. So you can give it like a big task and you say, hey, here's the data room, here's the review, here's my guidelines, here's the report. And then it like figures out all the different steps to just like one shot it. And if it has questions, it flags them to you. So it goes like sack, I need your input on this, this and this in order to produce a final report, which I think is transforming the way that it's reducing the stepping stone to get into it. It's me prompting the AI versus the I prompting me exactly. Yes. If you're unclear in your prompt, the AI will prompt you. It's going to go sack. You're very unclear here. I need to know this. And you're like, wow, spicy. All right. Like, there we go. Who's the best firm using LaGuara for M&A? LaGuara is the best firm using LaGuara for M&A. So we've made four acquisitions today. We're about to announce another one, I think today or on Monday. And we did our quickest deal. By the way, I'm happy to keep that under embark. We can keep that under embark. embargo because we're not gonna publish till after Mondays if you want to look and spoil that. Yeah. Well, the company's called Kedastral and they've built basically LaGuara for real estate asset managers and we had so much really saw eye to eye on like what the products should be and what the what like the taste elements here are and so they're seeding our New York engineering hub and the team has already joined and we're like full forces running out but back to M&A. Yeah, yeah, back to M&A and we did our quickest deal in I think 11 or 12 days and part of that was just like okay we have the bedroom like let's just use LaGuara to pass through everything we already know kind of what we're looking for and what we want to see you know doesn't exist and it's so insanely efficient and as you say yeah these are small enough deals to the point where we probably wouldn't pay like a like a big firm to do it anyways because it's just like doesn't make financial sense but it's so cool and I think it is to the pricing component really starting to to tie back to that and you have a couple of companies now coming out the YC that are like AI native law firms who are pricing basically doing like a series A or a series B at a pre pre negotiated price I think their price is like 25 grand like 30 grand is really low compared to what some of the TR1 firms are charting so again back to my earlier point of like AI will do what it can do if AI can do a good analysis of the bedroom which it can do it will do it and and then it will just take time for the market to price and package that properly I actually think a challenge on these on these deals are you not hiring outside council at all or do you have you are but it's only for the top it's only for the SP really got it so so this is this is very interesting to me because my my feeling is that as long as there are deals that are at a hundred million and above you're always going you're always going to want a human on top of that because of the stakes it seems to me now but maybe you know I sure does you know you today you know you we drive with with ways and GPS and trust it and we don't you know there really isn't as much of a of a human in the loop so I you know who knows but I think the one of the the reasons that that a firm might want to work with LaGoura is not just like the product but like hey transformation partner like help us plan for the future so what do you advise firms when it comes to things where you're looking at it and saying listen this this does look like work right now that you do that the work and the tasks themselves are going to change how do you help them prepare for the future so this is a big part of our work and we have a very large team dedicated to this right and the legal engineers I mean we have over a hundred of them in the company now this is their this is their job like how do we help the industry that we once worked in to change it starts at the top where you almost have to go okay firm X and tell us about your strategy like what practices are you really bullish on where do you want to win and where are you okay to maybe surrender some some land and then you almost need to go with the partners I found because it's very hard to do this across the entire firm at the same time you need to find the partners who on a lean in right and then you go okay let's take M&A as an example it's map out your process and you know pretty much it's it's like more less the same and then for each step here you you think okay how do we apply AI here now that's like that's like the beginner way of doing it I think the the super advanced way of doing it is huh assume we now have this technology where do we still need people like assume that we're do we still need people correct right like and like that's the that's the opposite framing of where can we put AI versus where do we still need like human judgment and where do we need human input and where do we need to guide our clients on you know people like people to people exactly like of course you're gonna have somebody responsible and accountable for the work and ultimately you know I would also want to buy a service from a person and not an agent and and I think we're starting to really see some practices and transform but it's not across the entire market it's it's partner dependent right we went out with this example with Deba voice for instance which which is public and what they're doing is they're taking a lot of their knowledge and they're packaging into our portal which then their private equity clients can consume self serve right and then there's going to be human escalation element to it so if a particular task requires human escalation it will escalate to a person at Deba voice do you think that do you think that clients will use law firms in a self serve kind of way because aren't these clients also buying products like LaGora yeah so so again like this goes back to the economies of scale thing one of the benefits that a firm like Deba voice will have is they serve so many clients on so many different problems that they have real data and knowledge and expertise that many of the in-house firms they work with actually don't have and so they can take that and package that to something that becomes very valuable right and and that's a thing that you can only get if you do it at scale so I think there will be I think there will be both is the is the true answer yeah yeah I'm I think what yeah go I'm sorry I was gonna say because the opposite side of this is working with the in-house council where you know incentives are really strong there's often like very top-down buy-in on we are going to transform our entire company with AI what does the legal team do and that I get so much energy out of because we can sit down with the GZ and we go all right let's look at contracting or let's look at your your patents or let's look at your licensing agreements or let's look at your litigation strategy and like where do where do you have work that you're currently under capacity to do or where do you have a lot of work that you think can be automated because ultimately we're automating legal work with with agents right and I think I started to see a pattern now where we're also moving from a user working with a chat like back and forth in just one single instance to running multiple agents in parallel and that's really cool because that's again something we've seen in our engineering team where the best engineers are running five parallel cursor or cloud code agents and now we're seeing lawyers in teams starting to do the same how similar is legal to code so the nice thing about like the reason why we're so advanced on code is because it's very easy to know if it's right or wrong right you basically compile the code you run the test and it's like code passes the compiler and it passes the tests you know checks everything all the green let's let's use the code in law don't really know if you are wrong until you get sued and so the feedback loop is so much longer and there isn't this like test that you just run and you're like yeah all compiles it's like good good advice like let's go for it and so it makes it I think much more important to serve it to people who know how to interpret the outputs if that makes sense so you know tools like like love able I guess everybody can code great everybody should code I don't think everybody should be their own lawyer yet oh I've seen I just said I just I just had a situation my my sister is starting a business and she's also simultaneously has recently gotten into AI and she's in that kind of like manic part of the adoption curve where you just start going oh my gosh AI for everything so she drafted a contract with someone and didn't include a termination clause and you know it's like there's lots there's lots of there's lots of things where yeah it can perform a task it doesn't it doesn't mean that like you should be doing that yeah right exactly and it's like we should vibe code but we should not vibe draft you know I think there's a reason why that's not a term yet and but I but I do think that there's so much demand for legal services in the world and this is you know a little bit to the you know does the work grow paradox yeah and the the truth is so much demand for legal services it's very supply constrained with the help of software supply will increase and the amount of legal work that happens in the world is going to massively grow and this will be amazing for everyone that The hard thing will be how do we, with sort of human intelligence and machine intelligence, serve that in an effective way? And I think ultimately, you know, that is the mission and our current focus. - You mentioned, you know, you're talking about the growing amount of work and this kind of comes back to the trillion dollar question. When legal spend itself is a trillion dollars, there's some people will hear, "Oh, wait, I think it's a trillion dollar company. "It is that main that AI is going to displace all of us. "Is Ligor eventually going to start its own firm "and put us all out of business?" When you, I imagine like other companies and law firms that are working with you may have some concerns, this is like a Faustian bargain we're making here. Are we like, you know, handing everything over and then eventually, so how do you think about the growing amount of work? Do we think that legal spend is going to go in excess of a trillion dollars? Like what's your view on the world? - It's so high, I think. You know, if you look at the legal service market or the legal market today, it's give or take as you said, a trillion dollars in total. Software spend is about four billion. So it's four percent software, 96 percent service. That's the highest quota between surveys, manual surveys and software in like any real large industry. - This is what I pointed out the Kirkland news. I said, it's less than one percent of the revenue. This hundred million dollars are spending this year. - So I think that software spend will grow from 4% to a normal amount, let's say 20%, 30%. And I think the trillion dollar will grow to double. Or let's say triple for the second. And so when that happens, you see two things happening. Well, okay, the original bucket was 40 billion. And let's say it grows to 300 billion. And then it doubles and it's then 600 billion. Okay, so the legal software market is 600 billion. And maybe this is like oversimplifying a little bit. But let's say a big portion of that legal I can serve very effectively then that can motivate a really big company outcome. And in the same way that Nvidia is selling shovels in the gold rush of AI, there are so many more talented lawyers in the world that I would love to serve and partner with. And I'm really good at building software. I would not trust my own legal advice. And I really enjoy that distinction because to me it's then very clear what my purpose and what the Gora's purpose in the world is versus what the purpose of the partners and the clients that we serve are. - We've gotten almost an hour into our conversation here and one of the things that we really haven't talked about we mentioned very briefly is Harvey. So I'm curious for your perspective on this because you're both obviously building this space. You both know what each other are building. I'm sure that you guys have plenty of access to the most recent versions of Harvey because you've got firms that are probably piloting both. So you both, it's everything's out there. Do you think we're gonna see your two products converge and become more and more similar over time? Or do you think that we're actually going to see as I'm starting to believe that your products will get drastically different over time? - So I tell the team at Gora that we are professional swimmers and when you're professional swimmer, you move a lot faster in the water when you're looking down at the black line and you're focused on your own race. And the competition moves a lot slower when they are busy looking sideways 'cause you got a much worse stream on your body. And the legal market I think is noisy and there are lots of companies. And of course we pay attention to what's going on but I'd say we actually take more inspiration from what's going on in other verticals like coding, right? Cursor and these tools for coding have probably come further than any tool in legal. I think that's a fair comment. - By the way, I was saying all of last year, I was saying the most important deal to pay attention to was not Harvey or LaGora. It was base 44, the acquisition of base 44 by Wix.com. This was a more important microcosm because for a lot of reasons, including the fact that what was happening in coding was likely going to then move into what was happening in legal. So I completely. - And so what does that mean for us? We wake up every day, we think about how we can delight our customers, how we can execute on the roadmap and then you try to have faster iterations like all that any other company in your market and that's what I wake up and I think about it every day. - Max, really great having you. We'll look forward to catching up following LaGora's journey. Really appreciate it. Thank you so much, Zach. This was wonderful. - See ya. - Thank you for tuning in to Zach Abramowitz's legally disrupted. If you enjoyed today's episode, please consider leaving us a rating in a review on your favorite podcast platform. Don't forget to subscribe, see you in never miss an episode. (singing) (upbeat music)