Uncapped #44 | Max Junestrand from Legora

At 23, with no legal background, Max Junestrand co-founded Legora to transform how lawyers work. Legora recently (March 2026) raised $550 million at a $5.55 billion valuation in a Series D funding round to accelerate its expansion across the United States. Over the past year, Legora has grown from 40 to 400 team members across the globe and the platform supports tens of thousands of lawyers each day across 800 customers in more than 50 markets. Max shares the story of building Legora, what it really means to build AI-native software from day one, why legal work is uniquely suited for AI, and how a small team from Stockholm convinced some of the world’s largest law firms to change how they work. --- Timestamps: (0:00) Intro (0:31) Legora's origin story (9:05) Building an AI-native company (18:16) No sacred cows, the models will be amazing (27:36) Winning pilots and global expansion (36:43) Starting in Europe (47:15) Stockholm culture and "blodsmak" --- Links: https://x.com/MaxJunestrand https://x.com/chetanp https://x.com/jaltma https://legora.com/ --- https://uncappedpod.com/ [email protected]

• 0:00Speaker 00

  I remember doing this interview in Swedish. There's a saying, like blood smock, and you're like, you taste the, like you taste the blood because you're, you worked so hard.

• 0:08Speaker 01

  Yeah.

• 0:08Speaker 00

  She publishes the article in English. At Legora, we wake up with a metallic taste of blood in our mouths. And people in the company go, holy shit, is Max a vampire? Or does he just floss badly? Like, what's going on?

• 0:20Speaker 01

  It's not like a culture that I think would quite work in San Francisco. Like, I don't know if that's something that you can do.

• 0:24Speaker 00

  Well, when we opened our San Francisco office, they're gonna taste the blood. And yeah, they're gonna taste the blood.

• 0:29Speaker 01

  I love it. Well, this is gonna be a cool new format. I'm here with my new partner, Chathen and Max. And Max, you're the founder CEO of Legora, which is an amazing legal tech company that Chathen sits on the board of. And so I just feel really lucky to be doing this with both of you. So you guys, thank you for, thank you for making this happen.

• 0:48Speaker 00

  Thank you so much, Jack. It's great to be here.

• 0:49Speaker 01

  Okay, so I want to start with the topic of competition. And Chathen, when you invested in the company, there were already competitors out there. This was, I think, it was only two, it's crazy because Legora is like-

• 1:00Speaker 00

  Yeah, two years ago.

• 1:00Speaker 01

  It's a big company already.

• 1:01Speaker 00

  Yeah, almost four hundred people.

• 1:03Speaker 01

  You know, but this, this, the seed was two years ago. And at the time of the seed, it was an early market, but there were competitors out there. And so I actually want to start with you, Chathen. Like, what was in your head at the moment you invested? Were you thinking about the landscape around? Like, were you just, Max is so special that I don't care? Like, what was going through your head when you did that?

• 1:21Speaker 02

  The first meeting that we had was with Max, was with me, Peter, and Max, actually in the other room. And interestingly, I had invested in two other legal software companies pre-AI.

• 1:35Speaker 01

  Oh, wow.

• 1:36Speaker 02

  And so there was a shape of the legal market that I intuitively understood because I participated in the market. And so I sort of understood the different kinds of lawyers, who buy software? Do in-house lawyers buy software? Do law firms buy software? How they, sort of, there was an intuitive understanding that I had. And there's sort of like two things that happen when you've, like, sold into an industry before. Either you end up hating it. Or you have some strong bias against it. So there was always this idea that there's opportunity for AI in the legal market. And you know, there was a player in the market that had already raised at a billion dollar valuation. And when Max came in to chat with me and Peter, the thing that immediately jumped out was the clarity

• 2:19Speaker 02

  of thought that Max had on why the general foundation models had a lot of room to grow in intelligence and how that was going to be a huge boon for the legal profession over the next couple of years. And so he had this like very strong viewpoint that there was something about legal data that the general models were going to serve in a very unique way.

• 2:43Speaker 01

  Max, since you're here, can you like explain like what was, what was that?

• 2:46Speaker 00

  So I think it's, it's worth to go back to 2023 and 2024, when I think part of the paradigm was you should train your own models. And like the general models aren't great and fine tuning is going to be really important. For two reasons, we were like, fuck that, right? One, fine tuning doesn't really seem to work, at least on the scale that we were operating, right? To train the new generational model, you had to put billions of dollars into it. And secondly, there was so much application that you had to build on top of the models to make them useful in your environment. And back then, I mean, just solving like basic data compliance, privacy and sort of

• 3:27Speaker 00

  great file uploads and like great parsing and great chunking and all of these things, that was where the value was.

• 3:35Speaker 02

  And there was another part of your experience, which was that you were actually embedded in a law firm.

• 3:39Speaker 00

  Yes.

• 3:39Speaker 02

  And so you were studying the shape of like what data law firms had in a way that was, you know, Bill talks about this a lot is like, does an entrepreneur strike you as a learn it all? And it was clear that the early Legora team, when we invested with like five people, they were just trying to learn everything they could about how the legal profession worked and they didn't have any bias towards it. And so the other thing Max said, which you should, you should share with everyone is because they were embedded in a law firm in a windowless conference room in Stockholm. Great. They had a deeper understanding, I think, of like how a law firm, like the data model of a law firm in ways that most of us didn't.

• 4:23Speaker 00

  And I mean, just to take you back even further, like when we started, I offered to buy a lot of lawyers lunch on LinkedIn because I wanted to learn. So like literally cold write them and say, hey, I'd love to meet. I'd love to talk about like IP law. I'll offer to pay you your hourly fee and lunch. And they were all too nice to like make me pay for lunch. They had often even not paying for it, right? But that did, as Jayden put it, like, I think it allowed us to work with customers from the very beginning. So the founding team at Legora were all engineers. The first lawyer didn't join until nine months into the journey.

• 5:00Speaker 01

  When you had a lawyer join, had you already sort of like set the plan and the goal for the company? Like, was that done without experts? And was that important to do without experts?

• 5:11Speaker 00

  This is actually funny. I mean, the founding, and this is a bit of the Legora Untold.

• 5:16Speaker 01

  First revealed here.

• 5:17Speaker 00

  First reveal, the company formation was in 2020. And there were four co-founders.

• 5:24Speaker 01

  I didn't know that.

• 5:25Speaker 00

  And I was not one of them.

• 5:27Speaker 01

  Didn't know that either.

• 5:28Speaker 00

  Right? They were sort of working on this intersection between AI and law for three years with the early BERT models. And even a Swedish trained version called SWE BERT. It was impossible to work with. Not only was it not very intelligent, it was also blatantly racist. Because I've been trained on like the Swedish like, like forums.

• 5:49Speaker 01

  Some racist data there.

• 5:50Speaker 00

  Some racist data there. When the LLMs like 2.5 came, that was when the moment shifted, right? And so we turned this into a company. Two of the co-founders left, I joined. And then we basically said, like, we're going to work in the intersection between AI and law. We don't know what that product is, but we're going to run like hell in this direction. And funny enough, the first lawyer who joined was a sort of soon to be customer of ours. So he was the CIO at one of the big firms in Sweden that we wanted to sell into. And he had built an early version. Of like a G P T plus the document management system. So basically, like an L L M that could rag into the existing precedent and data that the firm was using.

• 6:34Speaker 00

  And he basically said, well, these guys are going to run faster than me. And if you can't beat them, I might as well join them. And that turned out to be a good decision.

• 6:41Speaker 01

  Are you surprised by like how strongly the legal market has adopted A I? If I had thought, you know, in twenty twenty three, let's say, or twenty four, like, what's gonna really adopt quickly? Like, I don't know if personally I would have seen it coming that lawyers would be near the top of the list. I don't know. I mean, you've invested in stuff before too, so I guess this is for both of you. But like, has it been a surprise over the last two years, the rate of adoption?

• 7:04Speaker 00

  Yes, it's been like vivid. But but second, and maybe more importantly, the law firm market is very interesting because it's it's like this perfect equilibrium with frankly, like, pretty low differentiation. Like, if you need to do a V C deal here in the valley, like, you could go to any, you know, the top five firms and you're gonna get roughly the same thing. If one of them starts leveraging Legora to offer a better service at a better price point faster, all of them have to adopt it. So the equilibrium like shifts down and then everybody has to move. So what happened in the law firm market was as soon as one big firm in a market sort of adopted Legora and went public with it, everybody else had to do the same.

• 7:48Speaker 00

  That's not necessarily the same in the in-house legal sector, right? Like, if one big bank has it, like, another big bank doesn't necessarily need it.

• 7:55Speaker 01

  But was there something about the process of the way work got done or the structure of it that allowed Legora's product to drive so much value so fast in a way that it did force that sort of prisoner's dilemma?

• 8:08Speaker 00

  I just think the legal sector was so underserved with great software for such a long time that there was this like a lot of built up problems that we could easily solve with L L Ms, but they were really hard to solve like pre L L Ms.

• 8:22Speaker 02

  I also think you guys had a great insight early on, which was that there was like a deference and respect to the customers. That lawyers are really smart, they're extremely well educated, they're tech savvy. They're not programmers, but they're very tech forward. They use like the latest software, they use the latest devices. And so they were all gonna be playing with Chat G P T and Claude. And so if you showed up with a legal A I product, it had to be better.

• 8:48Speaker 01

  Than the foundation model.

• 8:49Speaker 00

  Yeah.

• 8:50Speaker 01

  Otherwise, they were just gonna say, why are you deserving of my dollars?

• 8:53Speaker 00

  And Microsoft Copilot rolled out very quickly, like every law firm in the world is a Microsoft shop.

• 8:58Speaker 01

  Yeah.

• 8:58Speaker 00

  Like, everybody works with Outlook, Microsoft Word, and, you know, where they store their documents, basically.

• 9:05Speaker 01

  What have you found, like, to the point of you have to be better than the models? If you had to break down, like, as a vertical AI application, what have been the things that have allowed you to just be so much better than the models that it's worth, you know, the incremental investment?

• 9:21Speaker 00

  So I think in the beginning, there was a lot of just foundational problems with the models. Like, you had to guardrail them very hard to make them useful. You had to build citations, you had to build good RAG systems, you had to overcome context window problems. And there was a lot of rate limits issues, so you had to, like, juggle different models for different types of tasks. There's just so many incremental, basic things to solve. I think as time has progressed, our product has moved further away from what the foundation models are and much more into this enterprise-wide platform, where, you know, we're gonna transact billions of dollars of legal work on the platform.

• 10:02Speaker 00

  And we've moved from building a lot of the agent work ourselves, and we sort of let the models rip a little bit more, like OpenClaw or Clawbot or whatever it's called these days, where, like with Opus 4.5 and Opus 4.6, there was an extraordinary difference in in level of intelligence and, like, instruction-following capability. And so I see our job as, let's provide the model the right environment and the right tools and skills to leverage, and then let's build a UI and an interface to the rest of the business so that they can all leverage it comfortably and with a lot of trust. I do think that, you know, the model capabilities improving so quickly makes us run faster,

• 10:45Speaker 00

  because we have to be three standard deviations ahead of any general capability.

• 10:50Speaker 01

  Yeah.

• 10:50Speaker 00

  And that's like a very good motivator.

• 10:52Speaker 02

  As somebody that's invested in a lot of software companies, like, one of the unique things about an AI software company is that it's tactically built differently than a traditional software company. And I think it's becoming more known now, but when you guys first started and you guys built up this org, the way you designed the org made a lot of sense for the product you were building and what you just described, which was like, we need to deeply understand model capabilities, and then we need to bring that to our customers in a way that's deeply differentiated, which, as you explained to me, meant we need to invest heavily in understanding the models, which then would lead to understanding what to build. But as models got better, your features may not matter in six months.

• 11:36Speaker 00

  Yes.

• 11:36Speaker 02

  And so, talk about how that led to an organization that was heavily technical, heavily engineering and researcher-led. And for a company as big as you are, you have very few product people. The number of product people you have essentially rounds to zero. You have like leaders, you have a couple of leaders, but that's it.

• 12:00Speaker 00

  I mean, the founding team, we were three engineers. And so, you know, the most natural hires were, let's grab all the smart engineers that we know from college and let's add them into the org. And in the beginning, you know, we had to build our own agent framework because like Lang Chin and these things that we initially built on, like, couldn't get customized to the level that we needed back in 2024. As we understood more about the model capabilities, but also of the problems we wanted to solve, like, let's take due diligence as an example. It's really hard to solve a due diligence task in a chat-based format because you need to review hundreds of documents. And hundreds of documents are never going to fit into the context window of a single model call, at least not back then, and, you know, probably not now either.

• 12:43Speaker 00

  So we built this new product that we call Tabular Review, big matrix where you would throw in, you know, tens of thousands of documents and you'd throw in all the prompts and it started running all of them in parallel. And what we basically did was we just said, okay, three engineers, you're now on Tabular Review. This is your own company, run. Over 10% of the EPD org at Legora are X Y Z founders. So our head of engineering, Jake, who joined, he was a solo founder in Y C. Our VP product, Adrian, was also a legal tech founder in Y C and happened to be both a G C and a lawyer. And so as we've progressed, engineering and product has sort of stayed at the core of who we are and what we do. And I also think that everything else is sort of an expression of that, like we can only market what we actually build.

• 13:27Speaker 00

  We can only sell what we actually build. And product lead compounds. I think as you put it in the beginning, we did not show up first. Like Legora was not the first product that many legal teams looked at because there were earlier entrants. So we knew that we had to show up and be best. And if you want to be best, well, then you need to invest in product. You need to invest in engineering. And I think you need to build that culture of like reliability first. We actually had a time period in the company for for six months where we didn't sell, basically, because we weren't ready to like hit the gas on onboarding a thousand lawyers a day and knowing that the product was going to keep up with that. So we took the early hits of like investing in that.

• 14:11Speaker 02

  Talk more about that period specifically. You know, the seed round you did with us was in March of 2024. The product went to G A October 1st, 2024.

• 14:21Speaker 00

  Yeah.

• 14:21Speaker 02

  And you called me early September 2024 and said, you need to come to Sweden because all of us need to sit in a room and just talk about where we are and what we need to do to get this thing out in a month. And, you know, we came and we sat the whole, literally the whole company, which wasn't that big back then. It was only 10 people. Yeah. And so it was like the whole company, the founders, chicken wings and beer.

• 14:47Speaker 00

  Yeah.

• 14:47Speaker 02

  And we, and peanuts, actually. Those were the three things served. And there was a very open dialogue of like, how do we get this thing out in 30 days? Because at that point, because you were essentially, you know, weren't facing the market test. You were building, there were 10,000 things you could build. And that the sort of like outcome of that discussion was that we're only going to focus on three use cases.

• 15:10Speaker 00

  Yeah, that's right.

• 15:11Speaker 02

  So talk about like, well, one, you know, you calling me to tell me to come to Sweden to have that discussion.

• 15:18Speaker 00

  And you actually showing up.

• 15:19Speaker 02

  I did show up. Reflecting on it, that was one of the most important things that that you did in the company and the founders did in the company was at that moment, say, we have thirty days to go. We're just gonna sprint at these three things, not the fifteen things that we could do.

• 15:36Speaker 00

  Yeah. So I think there was this feeling of like, you got these L L Ms, they're so powerful. We learn about all these use cases in the firms and with the clients that we work with. Let's go solve all of them. Like, wrong decision. Like, you can't solve fifteen things at the same time. And so we had to to kill a few darlings. And we had to like really double down on the stuff that we thought was gonna work. And we looked at on the market and we basically saw a few things that were really working, like as a paradigm for L L Ms in legal. One of them was this big sort of tabular extraction. Another one was embedding it deeply into Word and Outlook. So basically having Legora be accessible wherever the lawyer is already working.

• 16:19Speaker 00

  And we were still called Leia back then. Like, this was very early. We took the entire company, we had like a town hall. And I remember showing some numbers where like a particular company that just had one of these features were doing more revenue than us. We were doing like one point five million at the time. That felt very painful because we thought that we had a better suite. But we didn't have as much revenue because we were based in Sweden and we were sort of mostly selling to still European firms at the time. So we just said, let's do these three things. Let's do them better than anyone else and it's gonna be worth to buy our suite over anybody else's. And so I wrote this like very short product manifesto, send it out to the entire company. And we sort of rallied the troops. I think it was off the back of that, that we had our first quarter where we doubled revenue.

• 17:03Speaker 00

  So we went from like one point five to four. We're like, oh, this is like ripping and it's flying off the shelves. And then in Q one, we had another quarter where we doubled, where we went from like four to eight. Whoa, okay, now we're talking. And it became time to launch in the US. We hired Patrick and Evan, who joined from a competitor. And we sort of had our first boots on the ground in the US. And then we felt like, okay, what we have is like a winning formula. So we just need to crunch it out everywhere. And now I think we're at another interesting point in time where we've built all these different tools. But the paradigm from now onwards is humans are probably not going to work with all these tools.

• 17:48Speaker 00

  Like basically, agents will leverage the tools that we've built. So I remember early when MCP came, our CTO basically went, well, now Legora has two users. It's human users and agent users. And every new feature that we build has to be able to cater to both. And now we're seeing more people like basically use our agent that uses the tabular grid. Or like our agent who uses our word editing capabilities than humans actually going and using those features at all.

• 18:16Speaker 01

  Chatham made a cool point to me recently, which is that because you, we were talking about how, you know, companies that are pre-AI and companies that are just fully AI native just have to be built differently in various ways. And the fact that you didn't build a pre-AI company, I think, gives you sort of like, you know, this unshackled mind to like, you're not even trying to think about some past alternative. You're just like, given what's in front of me, what should a company look like? And, you know, you talked about how like having YC founders inside the company has been helpful. And I'm sure there's like a lot there, but I'm curious about like, what are like the main tenants that you've observed? You know, because now you've probably hired a lot of people who did, you know, work and build companies pre-AI.

• 18:58Speaker 01

  What do you think are like the main tenants, ideas, cultural concepts that have been important to you? Just to like make it work in like a fully AI native world?

• 19:08Speaker 00

  Yeah, so I think this idea that Chatham brought up around, like you have to be willing to like kill the stuff that you've done in the past is very important. Because I think in in more traditional software, you had to build the foundations and then you build the stuff on top of it. And you sort of kept building the stack. And in that world, it was also very good to have like a technical architecture where one feature would rely on the same microservices as like other features. But the problem is in AI, like maybe that feature now needs to scale really, really quickly. And the cost of writing software is so low that it's basically better to build your own stack for like each thing. And now that we hire, you know, finance professionals or even like lawyers internally

• 19:51Speaker 00

  to Legora, or we just hired our first like tax person. I think they come with a set of ideas of like, oh, this is how I used to do it in my old company. And everybody's forced to relearn, I think, and also question what their value is on top of the general model capabilities in a way, which is like very painful.

• 20:12Speaker 01

  Totally. Brett, Brett Taylor talked about this on this podcast too. Basically that like people are going to build something and six months later, we might just kill that thing and everybody needs to be comfortable with that, which I think historically would be a lot of painful internal conversations. Like, do you have to change, is that like a different culture for people?

• 20:28Speaker 00

  I think it's a different culture completely. I mean, I think the culture is you don't maximize for your function, like you maximize for the company always. And I'm very upfront with every exec who joins Legora that in a way, like you're joining with an expiration date and you have to continuously prove that you like scale out of that in a way, because the company is scaling so exponentially. And I don't know if it was Mark Zuckerberg or somebody talked about like, let's hire people with high Y slopes and not like high Y intercepts. I think about that a lot, mostly because I've had to do that, right? Like I did not join or start Legora with a lot of experience, but I've proven that at

• 21:12Speaker 00

  every new point in time, I've scaled with the business. And so other people in the Gora needs to do the same. And I think that goes for every function. And, you know, I think an engineering team that's shipping the amount that we do previously had to be like 500 people. And now we can get away with being 50. And I think there's even a question of like, do we need to be more than 100 engineers? Or is the bottleneck here really knowing what to build? And building it in the right way? And designing an experience that works for, you know, hundreds of thousands of people that we now have on the platform? I think the paradigm is like shifting all the time.

• 21:52Speaker 00

  What's nice about our work is that engineering is sort of a roadmap of what's going to happen in other industries too. Like I think the general models have come the furthest in coding, but also those organizations are very quick to adopt and shift. And so like engineering orgs are today looking slightly different. And I think we can expect the same in, you know, legal organizations.

• 22:15Speaker 02

  Two things you brought up that you should be great if you could dive into. One is Legora doesn't really have a long-term roadmap. Like you guys react and build today. And, you know, when you first got started, you had this like nearly weekly cadence where that's how long you would roadmap to. And these days it feels like you almost roadmap on a daily cadence. And so like things change tomorrow. Like you wake up and it's like, we have to do something different. Talk about that lack of roadmap. And then also the other thing that you've invested heavily in is just understanding model capability and the sort of proprietary eval infrastructure you've built where you've had these conversations with the foundation model companies of how you're

• 23:00Speaker 02

  able to identify latent model capabilities that they themselves are not aware of.

• 23:06Speaker 00

  I mean, our roadmap, like way back, every new model just like unlocked new things, right? And when we got early access to G P T like 4.5 and you just realized that holy shit, like now it can finally draft like an end-to-end thing. And we don't need like all these harnesses and like things around it. That's amazing. Like let's unleash it in a way that that works.

• 23:28Speaker 02

  By the way, to do that, you need sort of like a low ego organization.

• 23:32Speaker 01

  Totally.

• 23:32Speaker 02

  You build all this IP and all this software.

• 23:35Speaker 01

  Yeah.

• 23:35Speaker 02

  And you're like, okay, now the model can do it.

• 23:37Speaker 01

  Yeah.

• 23:38Speaker 02

  Delete it all.

• 23:38Speaker 01

  You worked really hard for six months.

• 23:40Speaker 02

  Yeah.

• 23:40Speaker 01

  We're deleting everything.

• 23:41Speaker 02

  Yeah, it's incredible.

• 23:42Speaker 00

  Yeah, but I think a lot of the things that we have built, we know that we're gonna delete someday.

• 23:47Speaker 01

  And I guess you kind of need people to opt into that at the front end for that culture to really work.

• 23:51Speaker 00

  We've also talked about it as like, if we were, if we're here today and we start building for the future that's over here, like, that's too far out. Like, our customers are not gonna adopt that. They don't understand it yet. So we need to take them on the journey and we need to take them on the path of being successful, which I think every iteration cycle now is shorter. Like, back in 2023, 2024, I think it was like slightly longer. Like, you'd have a quarter or two quarters because the models weren't moving that fast. Every upgrade was pretty incremental. But now it's like flipped. Opus 4.6 flipped in capabilities. So now we have to revisit a lot of the things that we built.

• 24:28Speaker 01

  Do you know what the next flip you're waiting for is? Like, is there a thing?

• 24:31Speaker 00

  So actually, I don't think, so it was funny. I was at the Customer Advisory Board at Anthropic yesterday, which is, I'm wearing my Dario shirt here.

• 24:38Speaker 01

  You look like Dario.

• 24:39Speaker 00

  Thank you. Most of that conversation was about the models are now intelligent enough where they're no longer the bottleneck. The bottleneck is all of the software around putting the models in an environment where they can execute and do work and humans can review that work in like a trustworthy way. They're seeing that across basically every single vertical and every single company. So I don't really think that we're waiting for new model capabilities anymore. There's like nice things to have, like it's nice to have better context windows. It allows us to, you know, do less garbage and context management. Or when you overflow the context in memory and so on, you have to like deal with it to refresh it. So there's nice to haves.

• 25:23Speaker 00

  But I think we're at a point now where we just have so much building in front of us in terms of bringing the model capabilities into our world, that that's where all of our focus is. I think on discovering what the models can do, we thought very early on that evals were going to be important. And both building up like an exercise of building new evals, but also building out evals for all the use cases that we want to cover for. Because in the beginning, it was a lot of like, oh, how's good this? How good is Sonnet? How good is Gemini? How good is GPT? And so we had to test them on the different evals. And a lot of our customers actually contributed this. So they would give us manual tasks that they used to do. And they'd tell us, here's the evals.

• 26:05Speaker 00

  And we're going to call you when we can get to 100% on these evals. And I actually remember it was a funds-related use case, an LPA key term review report that a Danish law firm was spending like three days on, basically. Like, an associate would spend three days putting together that report. In summer of 2024, we had like 60% accuracy on that task. By the end of that summer, we had 100% accuracy. And once you got to 100% accuracy, I mean, that task is done. Like, it's over. I've adopted this mentality internally that if AI can do something, it will do it.

• 26:45Speaker 00

  And so our product, like, we think a lot about solving legal tasks end to end. And once a task is conquered, it's done. Like, we'd just like strike it out. And we're on this path of solving more and more complex tasks. Like, you start with NDAs. But at some point, you get to full-on share purchase agreements, which are very complex. But we're going to get there. I think the question for these organizations who are maybe more traditional and trying to keep up with the pace of AI is, how do you do that while at the same time do your normal job? Right? I think a lot of the organizations that we work with really struggle with. Keeping up with the technology uplift, even like our developments.

• 27:28Speaker 00

  And so we're, you know, we're struggling by getting all the latest models. And then we're turning that into product and they have to adopt it. And then their customers and it's, yeah.

• 27:36Speaker 01

  There's a question, I think, for both of you. As I'm listening to you talk, I'm sort of like, you know, I can sort of see the, you know, the hill climb that you're on where you've like attacked, you know, one part of it. And the next one's coming and the next one's coming. And, you know, one of the things I'm thinking about is for, let's say, a new startup in legal, what would the right strategy be for them? Like, how do you possibly get into the mix fast enough for all of these things?

• 27:59Speaker 00

  Exit to Legora.

• 28:00Speaker 01

  Exit to, sell to Legora, that's a good one. How urgent is it to grow really big, really fast for Legora, given all of the dynamics around? Chaitan, I'm curious, like, how do you think about this? Like, is it the same urgency as always? Or do any of these dynamics mean that, like, getting to real scale is more urgent here than other places?

• 28:20Speaker 02

  We can go back to sort of launch day, October 2024. So when, when they launched, you know, roughly the AR of the business was rounded to a million dollars. If you just go back into that moment, you know, there was this exercise of should we make a budget? And, you know, what, what we all decided around the table was there was no reason to make a budget because we don't know anything about the market. We don't know if people even like our product. We had instincts, but like, we just needed to go literally as fast as we could to get the product as in many hands as we could. Because ultimately, the whole theory of the company didn't work until we got product feedback. And so that was literally the aim.

• 29:03Speaker 02

  The aim was like, get this out as quickly as possible in as many hands as possible. And I think one of the things that Max did, again, this is like, it's cliche to say it's first principles thinking, but it is because it's like, the team was unbiased by how to build a software company. And so one of the things that you learned in SaaS was the way you do pilots is like, you would go in, do like a time trial pilot where you would like give them access to the application. And the minute the trial was done, you would turn it off and. Then they would have to make a purchasing decision. A big thing that happened with Legora is they would go put Legora into your organization.

• 29:47Speaker 02

  And whatever you put into Legora, they would like leave behind, even if you didn't want it. And so there was this idea that like, hey, you adopted AI, you did stuff with AI, you built some practices. But you're not like, whatever skills you built, or whatever IP you built, it's kind of yours. And like, we can leave that behind. It's not a big deal. It's like, it's your skills, it's your things that you've learned. And then Max went around and just gave people like 30 day pilot, 60 day pilot, whatever they wanted.

• 30:14Speaker 00

  They would run these competitive pilots, right? So they would say, okay, there's a couple of companies on the market. We're gonna want to A B test all of them because it's really hard to pick just, you know, based on the features that on your website. And in those pilots, I think we did an extraordinarily good job of delivering value. And so when the sort of 30 days were up, like if we shut it down, it would be a riot. Right? Like people would roar and they'd be like, we've never seen software adoption like this in a legal organization. And we need this and we, you know, we need it now. And in those pilots, we would demonstrate much better than any other company. The value that the product and the service around the product could bring.

• 30:57Speaker 00

  So we hired all these lawyers who are now called legal engineers. It's a great term, I think. Forward deployed legal.

• 31:05Speaker 01

  I was just gonna say, what about FDLE?

• 31:06Speaker 00

  FDLE, that's right, FDLE. And they're amazing. Like they're the most tech savvy lawyers in different organizations. Who don't want to make partner because like, you know, that's one type of life. And they want to work in a tech company. And now they get to work with their practice that they're amazing at and technology. And then they get to work with the best legal organizations in the world and like driving that change.

• 31:28Speaker 01

  And I would think once you're embedded in these organizations, it's gotta be sticky.

• 31:32Speaker 00

  I think Legora is very sticky. We've ripped out our competition at many.

• 31:36Speaker 01

  What creates stickiness?

• 31:38Speaker 00

  So the stickiness is the use cases and the cadence. And, you know, if you've invested time in building up a work. Workflow that like works for you, why would you wanna switch?

• 31:49Speaker 01

  So is it that, is it?

• 31:50Speaker 00

  Is it, it's usage?

• 31:52Speaker 01

  It's not data.

• 31:53Speaker 00

  No, not yet. And not, not any real technical implementation, which is great. Because our competition has been deployed in a lot of places that sees no real usage or very simple use cases, which means that we can go there, show them and display clearly in a pilot that we deliver much, much better, and then we can easily swap it.

• 32:16Speaker 01

  Hmm.

• 32:16Speaker 00

  So we actually have a dedicated like migration team moving deployments over to Laguardia.

• 32:21Speaker 02

  And I think this is where we often talked about not only product engineering velocity, which came naturally to the founders here because they were engineers, but also this idea of velocity of customer interaction, which was like, if a customer wanted to buy a certain way, wanted to do a pilot, whatever.

• 32:40Speaker 01

  Mm hmm.

• 32:41Speaker 02

  Just don't add friction. That was actually the key unlock, which was like, there was this idea of let's just go get this in everybody's hands and not to have any bias. And so one of my favorite stories about Max is that he came to San Francisco to sell a bunch of clients and then, you know, he texted me and he was like, are you free for dinner? So we met for dinner and then he asked for a ride to the airport. And I casually asked, where are you going, expecting to say Seattle or LA or something? And he was like, I'm going to New Delhi. I was like, why are you going to New Delhi? He goes like, well, like one of the largest firms in India wants to buy. So I figured I'd like go give it to them.

• 33:18Speaker 01

  That's crazy.

• 33:19Speaker 02

  And so, you know this, in SaaS, it was like, no, like do the West Regional.

• 33:25Speaker 01

  Yeah.

• 33:25Speaker 02

  Then do like the East Regional.

• 33:27Speaker 01

  Yeah.

• 33:27Speaker 02

  Then do like Western Europe and then eventually hire an APAC head. And then it was like this thing.

• 33:33Speaker 01

  Yeah.

• 33:34Speaker 02

  And because this company didn't.

• 33:35Speaker 01

  And by the way, there's gonna be like a year of engineering work to be even kind of ready to serve India.

• 33:40Speaker 02

  Yeah. And because like this company and this team had never built a pre-AI software company, they didn't know they weren't supposed to go sell in India early, like one quarter into like selling the product. So Max got on a flight, went to India and a customer in India bought. So it was one of those things where like. Because they didn't have the patterns, they were able to get big globally in parallel.

• 34:07Speaker 01

  You know what I also wonder on this? We've talked about this a little bit, that like being a Europe-based company means that you are multinational from the beginning.

• 34:15Speaker 00

  You have to.

• 34:16Speaker 01

  And I think this, I'm sure some of this is pre-AI, and I think, I mean, a lot of it is. I also think there's a thing where like, if you started in Europe, you've already learned how to sell to 10 countries and you know that there's differences in the way that the cultures work and the way they purchase software and what the rules are and the regulations and these things.

• 34:36Speaker 00

  Yeah.

• 34:36Speaker 01

  And so I'm curious if you thought about that when you invested and you're like, well, actually, maybe coming to the US will be easier one day. I'm curious your experience on that, but like.

• 34:44Speaker 00

  I mean, Y Combinator weren't particularly excited about backing a company in Sweden.

• 34:48Speaker 01

  Yeah.

• 34:49Speaker 00

  I remember the first interview with Gustav, and he, and he's Swedish, like a Swedish partner at YC, and he goes, so you're gonna move to the States, right? And I go, yes, yes, of course. Like, that's the cue to say yes, so that you get the invite to go to YC.

• 35:02Speaker 01

  You're a Macam gun, Sweden. You guys are operating Sweden after YC.

• 35:06Speaker 00

  And then I came to YC and I left three days later because I had so much business going on in Sweden and I couldn't do work between 1 a.m. and 10 a.m. Like, that was just impossible. But, you know, yeah, like, the Swedish legal market is smaller than Kirkland and Ellis. So, of course, you have to expand.

• 35:23Speaker 01

  Yeah.

• 35:23Speaker 00

  And naturally, we went to Finland. And then we went to Denmark. Then I was like, well, I think we got the hang of it. And the most important thing was, like, the first customer we got, Manheim or Svartling, the big firm in Sweden, their managing partner had such a good relationship with the other firms in other non-competitive countries, that he would just introduce me. And I would fly down and I'd say the same thing as I told him, like, AI is gonna change the world and you're gonna need a partner. I'm here, let's work. You know, that sort of made it, made it all start. But then, the, the move to the UK and the US was like when we really started ripping.

• 36:01Speaker 01

  How different was coming to the US versus going to Finland?

• 36:03Speaker 00

  Not at all. I, I had a rule. So, there's actually a few Swedish companies that tried to go to the US but did so unsuccessfully, like Klarna. They tried many times before they, like, actually made it work. And. My rule was if we can serve two of the biggest clients in the world or in the US from Stockholm, then we're ready and then we'll open an office here. So Clary Gottlieb, amazing Wall Street firm, and Goodwin and Procter. And we served them both. We won their business in competitive pilots. And we could serve them from Sweden. Like, we did a lot of flights back and forth. But after they signed, we said, okay, amazing. Now we're ready. Let's open an office here.

• 36:43Speaker 02

  So one thing about the market structure of legal that we knew about here at Benchmark ahead of investing is that legal has this unique market feature that it's a services industry. And in services industries, technology adoption is slow at first and then rapid later. So if you just look at any marketplace idea in a services area, it's like the marketplaces are usually like supply constrained. And then the minute supply unlocks, all of the supply comes online into the market. And then you become demand constrained. And so if you study marketplaces, especially marketplaces around services,

• 37:24Speaker 02

  this is something that you just like fundamentally learn as like one of the rules of marketplaces. And so in legal, the market structure is such that like the initial adoption will be very slow and hard. But once it unlocks, it like really unlocks. There's some kind of like exponential viral coefficient that happens there. That's one part about the legal industry that's really interesting. And then how it overlays into software in legal is that if you look at the most successful legal software companies, they were all started in Europe, pre-AI too, by the way. I had a hypothesis that part of the reason why you get that way is that you're used to selling the multi-geography and multi-rule systems from day zero. So for example, Legora sold to a Swedish firm.

• 38:09Speaker 00

  Yeah, that makes sense.

• 38:10Speaker 02

  And a Spanish firm and a Finnish firm. And so, yes, they're like laws at the European Union level.

• 38:15Speaker 00

  Yeah, but like from the beginning, it needs to work for many people.

• 38:18Speaker 02

  That's right. And if you start in the US, what you end up designing is that there's the federal legal system. There's a state legal system and then there's regional. But it's not as bifurcated as like literally different countries.

• 38:32Speaker 00

  And different languages.

• 38:33Speaker 02

  And different languages. And so you build all this stuff on day zero. That you don't if you start in San Francisco. And one of the interesting things that Max showed us in the prototype in the first meeting is he had multi-language support already built and he had like multi-legal framework support already built.

• 38:52Speaker 01

  I remember I demoed Sweden and Spain.

• 38:55Speaker 02

  That's right. And that was like remarkably impressive because it was it was a company with five people thinking global scale.

• 39:03Speaker 01

  Yeah.

• 39:04Speaker 02

  Because they were forced to because they couldn't serve the Stockholm legal market.

• 39:08Speaker 01

  Totally.

• 39:09Speaker 02

  Those two things just meant from they launched the product, they got a bunch of people to sign, that immediately it was like, let's go get the two big firms in every geography because we have to.

• 39:19Speaker 01

  And it was global from day one.

• 39:20Speaker 00

  And now, I mean, Legora, I think, has become a hub in like a technology hub in Europe. Like, people from Germany, from the Netherlands, from Spain, from Italy, they're all moving to Stockholm, even in the winter.

• 39:34Speaker 02

  So talk about talk about the culture part of it, which I think stands out a lot. And so it's hard to describe to people what it's like to visit the Legora office.

• 39:43Speaker 01

  When you came back from a Legora visit recently, you were like, oh, my God, they are so good. Like, something's going on there that I haven't seen before.

• 39:50Speaker 02

  Right.

• 39:50Speaker 01

  It sounded different. I don't know if it's Legora specific or if it's like something that is, you know, happens in Sweden that can't happen in America, but like you were affected by it.

• 39:58Speaker 02

  It's true. Initially, even in the group of five or in that group of 10 in September of 2024, or group of 15, however, how big the company was, there was like a a common thread amongst everybody. They were like deeply technical, deeply intense, and a desire to win. And they were like thinking globally from like day zero. And because they were in Stockholm, they also decided to recruit all over Europe from day zero to bring people to the Stockholm office. And so what ended up happening is I think you end up becoming a magnet for anybody that wants to build at the forefront of AI with a level of intensity and determination, this idea of like wanting to win.

• 40:40Speaker 01

  But so like, what did it feel like to you? On your recent trip, there's like a few hundred people in there. Like, what did that feel like?

• 40:44Speaker 02

  The level of engagement and buy-in.

• 40:48Speaker 02

  To the company mission was truly unique. And I think the company has done a great job with this idea of building for the company. And I really do think building an AI company is like a real test in ego. It's like you literally can't have an ego because you have to have this idea that AI is just gonna do this.

• 41:12Speaker 01

  It's gonna be better than us at everything at some point.

• 41:14Speaker 02

  And they're gonna, it's just gonna do this. The foundation model will do this capability. And I'm like puzzling through this and it's really hard and it's an amazing feature. And you know, we have these high bars of quality and polish. So we're gonna like ship fast, work really hard, build this amazing feature. And it's gonna disappear within 12 weeks. Requires an extreme amount of buy in and an extreme amount of humility that like, we're just riding this massive wave and we don't know where it's taking us. But like every day we solve today's problems and we don't worry about tomorrow because it's a different world. There's a different type of energy buy in cadence that comes with that culture. And I think that it's really interesting.

• 41:55Speaker 02

  The disadvantage of Stockholm has now become La Gora's advantage of being in Stockholm, which is that their talent population that they, that they get to hire from is not just in Stockholm. It's all over Europe and now it's like all over the world. Because anybody that has that attitude is welcome to come join Stockholm.

• 42:16Speaker 00

  I think our competition is, you know, has remote days, like three days in office. Everybody leaves at six. Like from, from very early on, like we serve dinner at eight every day. A lot of people in, in our region are sort of tired about like all these big American winners. And we know that we have the talent and the grit and the prerequisites to build a generational company. Like, yeah, we had to go to the US to raise money because we want to work with the best businesses in the world. But. Like, there is a, a, a level of like, we can also do it, right? And we, we have Spotify just down the street.

• 42:59Speaker 00

  How are you gonna get this level of fervor in the US? I think we have. I think we have a very unique culture in our New York office. Is it different? It's very different. Like, people, well, it's not different from Stockholm. Oh, okay. But it's. We seeded it with, you know, the culture carriers from Sweden that came to New York. And I spent.

• 43:16Speaker 02

  I think tactically, this was a really cool thing they did, which was, I think, like, you should tactically talk about how you make everybody interview in Stockholm.

• 43:25Speaker 00

  Yeah.

• 43:26Speaker 02

  And then they have to onboard in Stockholm.

• 43:27Speaker 00

  Oh, wow. So you live in New York, you're gonna join the New York office, you're going to Stockholm? Onboard in Stockholm. Yeah. People who join in Sydney have to go on a 24-hour flight to onboard in Stockholm.

• 43:37Speaker 02

  So you can't onboard anywhere else but Stockholm.

• 43:40Speaker 00

  Yeah.

• 43:40Speaker 02

  And then, when they first opened the first international office, which was New York, and actually London, too, you did this with, which is like, people that were based in Stockholm, moved.

• 43:51Speaker 00

  Yes, seeded.

• 43:52Speaker 02

  To those offices to set a cadence. It was like, it's all gonna be the same as Stockholm.

• 43:56Speaker 00

  And like, the Germans who joined Legora, like, they have to move to Stockholm, and they'll work here a year, and then they can move back to open the, the German office. Yeah. Like, you have to get it right.

• 44:06Speaker 02

  It's a fascinating thing where, you know, I've been part of many companies that have many offices, and every office tends to take its own character. And I remember the founders of Legora saying, we want every office to feel the same, which was itself a different way of thinking. Every time Max has had me visit the company, I visit during dinnertime, which is 8:00 PM. Like, that's when they have guests, is like, 8:00 PM. And that's been the case in every office. And so that's another, like, thing that happened at this company. And it, it's interesting to me that it continues to scale, which is like, you can continue to onboard in Stockholm, because like, every, the 400 people that joined before you onboarded in Stockholm.

• 44:51Speaker 00

  Yeah.

• 44:51Speaker 02

  So you should too.

• 44:52Speaker 00

  I mean, the only reason why we have that rule was because I did an internship at McKinsey, and we'd have dinner at it. So I was like, I guess that's how you do this.

• 45:01Speaker 01

  Totally. It's also like in some ways, doing the US office in New York. Obviously, it's not like it's some outsider city, but from a tech perspective, there's a lot of people in New York who are like, I want to work at like a great tech company. And you know, there's obviously been more there than in Stockholm, but it's still different than San Francisco. And so I think you could probably bring some of that cultural thing there as a result of that.

• 45:21Speaker 00

  Yeah, and now we just opened in Houston and we're opening in Chicago. It's all the big legal hubs. Is this correct? Did you do a reference with Daniel Iac? Yes. Yeah, and I think I heard this from you. You asked him about like, what is the culture at Leia? And I think he said something like, they're pretty intense. That's right. We were very upfront with that even in interviews. And not intense to the point where it's like, not fun. But like coming, like showing up as number, like being number two in this space is like not a outcome worth fighting for. Like then we might as well go do something else. Like, we're only gonna play here to win.

• 45:58Speaker 01

  You think number one, number two will just be vastly different outcomes?

• 46:01Speaker 00

  Oh, yeah, completely. And it doesn't actually matter if that's the case or not, but that's the way I think.

• 46:06Speaker 01

  Gives you the right mindset.

• 46:07Speaker 00

  Yeah, like I think everybody's dialed into that. And I remember doing this interview in Swedish and there's a saying that you like, like blood smock, and you know, like you taste the, like you taste the blood and because you worked so hard.

• 46:23Speaker 01

  Yeah.

• 46:23Speaker 00

  And I basically told her in Swedish that, yeah, you know, sometimes I wake up and, you know, it's a Swedish saying, so it made sense.

• 46:29Speaker 01

  You're so woke up, I taste, I have too much coffee, I taste the blood.

• 46:33Speaker 00

  And then, and then she publishes the article in English.

• 46:37Speaker 01

  Yeah.

• 46:37Speaker 00

  And the saying doesn't make any sense in English.

• 46:39Speaker 01

  It's like Max is bloodthirsty.

• 46:40Speaker 00

  No, it's like the Legora founders make, wake up, at Legora, we wake up with a metallic taste of blood in our mouths. And people in the company go, holy shit, is Max a vampire? Or does he just floss badly?

• 46:52Speaker 01

  And what's going on? And what, how do you feel about that now?

• 46:54Speaker 00

  Now it's become this thing, like the Americans are hashtag blood smock. Like it's, everybody's in on it. It's amazing.

• 47:00Speaker 01

  It's a cul- I mean, it, I can like feel the energy of it. It's not like a culture that I think would quite work in San Francisco. Like, I don't know if that's something that you can do uniquely.

• 47:09Speaker 00

  Well, when we open our San Francisco office, they're gonna taste the blood. Yeah, they're gonna taste the blood.

• 47:14Speaker 01

  I love it. All right, my last question is, you just raised a big round.

• 47:18Speaker 00

  Yeah.

• 47:18Speaker 01

  Which is awesome, congrats. What does this mean for the future? What's coming?

• 47:22Speaker 00

  Well, maybe first off, just to give you a bit of insight into the round, like every round at Legora since Chatham has been a preempted round. I don't think I've ever actually gone out to like fundraiser since you did the round. Yeah, it's been, it's been very pleasant. We actually also have a history of taking the like lowest term sheets. Um, I remember taking, like, we were actually, so this is funny. Like, we were negotiating the number of shares that Chatham was gonna buy on Excel in front of us. And he goes, I've never ever bought a company where I didn't get 20%. And I go, well, I'm never gonna dilute more than 17.5. And we sort of look at each other and go, well, I guess we're in a, in a bit of a stalemate here.

• 48:05Speaker 00

  It was like the immovable object meets the force. And so we like just put on Excel, we write down the exact number of shares and we start going decimal by decimal.

• 48:15Speaker 01

  Wow.

• 48:16Speaker 00

  Until we're both.

• 48:17Speaker 01

  That's such, that is so legal coded, like, just the nerdy Excel.

• 48:22Speaker 00

  It's, it was wild.

• 48:23Speaker 01

  It's perfect.

• 48:24Speaker 00

  You end up investing like 9.521 and we're both equally unhappy or happy.

• 48:30Speaker 01

  That's great.

• 48:30Speaker 00

  I think we were both happy.

• 48:31Speaker 01

  That's a beautiful way to start.

• 48:32Speaker 00

  We're both happy. But the Series D has been really great because it's the first time I've done it together with, with someone else. So David, our CFO, who just joined from Vanta, he's an absolute monster. It was funny, we had our, our company-wide kickoff and you get to like pick the song you wanna walk out to. And he goes, Max, I want Monster by Kanye West. And I go, okay dude. And it's like the lights drop and I'm like, I have a big surprise for you, everyone. Like David is joining as our CFO and like the speakers just explode with this like, and I don't know if you've heard the song.

• 49:09Speaker 01

  Yeah, of course.

• 49:10Speaker 00

  It's like starts and everyone's like, holy shit, what's going on? And he like comes up on stage and he's just like so much energy. And in the references, people refer to him as a CFO. And I was like, that's amazing. So he and I did the round, it was super fun. It was the first time we went out to actually do a fundraiser. We had a, we had a deck this time and it was wildly oversubscribed. I think we ended up having like 1.5 billion in demand for the round.

• 49:37Speaker 01

  It's a lot.

• 49:37Speaker 00

  It was crazy, but we're super thrilled about Excel, coming in and leading it. Some great participation from Manlo and Bain. You know.

• 49:45Speaker 01

  Well, it's awesome. It's a huge testament to what you've done and super exciting. And I think you're you're just getting started. So Max, thank you for doing this. Chatham, thank you as well and really enjoy it.

• 49:54Speaker 00

  Thank you so much, Jack.