# Building an AI-Native Software Company With Legora CEO Max Junestrand | Ep. 44

Markdown copy of https://realalpha.app/v/DdHl7dXVt-w/ on Real Alpha, the best minutes from long interviews with the people building AI. Cite and link the page, not this copy.

Max Junestrand says AI-native legal software wins by putting fast-improving models inside trusted workflows, then rebuilding as capabilities shift.

- Show: Uncapped
- Hosts: [Jack Altman](https://realalpha.app/people/jack-altman/) & Chetan
- Guest: [Max Junestrand](https://realalpha.app/builders/max-junestrand/) is cofounder and CEO of Legora.
- Published: Mar 12, 2026
- Length: 50 min

## The best minutes

- [14:01](https://realalpha.app/v/DdHl7dXVt-w/?t=841) [Focusing on three use cases helped Legora double revenue](https://realalpha.app/s/focusing-on-three-use-cases-helped-legora-double-revenue/) (4 min)
- [22:52](https://realalpha.app/v/DdHl7dXVt-w/?t=1372) [Legora uses customer evals to decide when a legal task is solved](https://realalpha.app/s/legora-uses-customer-evals-to-decide-when-a-legal-task-is/) (5 min)
- [29:04](https://realalpha.app/v/DdHl7dXVt-w/?t=1744) [Legora won pilots by letting customers keep what they built](https://realalpha.app/s/legora-won-pilots-by-letting-customers-keep-what-they-built/) (3 min)

## Also worth watching

- [18:03](https://realalpha.app/v/DdHl7dXVt-w/?t=1083) [Legora expects executives to scale as the company changes](https://realalpha.app/s/legora-expects-executives-to-scale-as-the-company-changes/) (4 min)
- [33:54](https://realalpha.app/v/DdHl7dXVt-w/?t=2034) [Legora proved US demand from Stockholm before opening locally](https://realalpha.app/s/legora-proved-us-demand-from-stockholm-before-opening/) (6 min)
- [6:27](https://realalpha.app/v/DdHl7dXVt-w/?t=387) [One law firm's AI advantage can push its peers to adopt](https://realalpha.app/s/one-law-firms-ai-advantage-can-push-its-peers-to-adopt/) (3 min)
- [10:41](https://realalpha.app/v/DdHl7dXVt-w/?t=641) [Legora kept engineers at the center of product development](https://realalpha.app/s/legora-kept-engineers-at-the-center-of-product-development/) (3 min)

Skip the opening investor and origin-story discussion, the Stockholm office-culture anecdotes, and the Series D fundraising close.

## Full analysis: Max Junestrand says a legal task rose from about 60% to 100% accuracy

- One Danish law firm's review task moved from about 60% to 100% accuracy in a summer.
- That customer-defined benchmark is concrete, but the episode gives no scoring rules or broader validation.
- For buyers, the test is whether their own workflows pass repeatable checks as models change.

Its 6 sections, what it means for you and what to watch are on [the page](https://realalpha.app/v/DdHl7dXVt-w/#analysis), free with an account:

- [3:01](https://realalpha.app/v/DdHl7dXVt-w/?t=181) General models moved the fight into trusted workflows
- [15:07](https://realalpha.app/v/DdHl7dXVt-w/?t=907) Three use cases sharpened Legora's market test
- [26:30](https://realalpha.app/v/DdHl7dXVt-w/?t=1590) Customer evals made task results concrete, not universal
- [29:11](https://realalpha.app/v/DdHl7dXVt-w/?t=1751) Open pilots lowered the cost of trying Legora
- [23:35](https://realalpha.app/v/DdHl7dXVt-w/?t=1415) Legora builds expecting its own work to disappear
- [36:13](https://realalpha.app/v/DdHl7dXVt-w/?t=2173) Stockholm gave Legora a test before US expansion

## Summary

At 23 and without a legal background, Max Junestrand co-founded Legora to transform how lawyers work. He joined a Stockholm team working at the intersection of AI and law and helped turn it into a company that grew to nearly 400 people.

Junestrand argues that legal AI companies should build trusted workflows and tools around general models rather than rely on training their own models. He says Legora's engineering-led organization adapts quickly, tests model capabilities against customer tasks and is willing to replace work as models improve. Junestrand and Chetan describe how open-ended pilots, legal engineers and low-friction sales helped Legora win customers and expand internationally. They also discuss how Legora's Stockholm culture and European roots shaped its product and global operations.

### Minute by minute

- [0:35](https://realalpha.app/v/DdHl7dXVt-w/?t=35) **General models changed the legal AI thesis.** Chetan says his experience investing in legal software helped him understand the market, while Junestrand says Legora rejected the idea of training its own models. He says the early opportunity was to make general models useful in law firms by solving problems such as data compliance, file uploads, parsing and chunking.
- [6:27](https://realalpha.app/v/DdHl7dXVt-w/?t=387) **Legal firms face pressure to adopt AI.** Junestrand says lawyers adopted AI faster than he expected. Chetan argues that when one major law firm adopts a tool and offers better service, faster and at a better price, competitors feel pressure to follow. Junestrand says legal had been underserved by software, while lawyers were already comfortable trying tools such as ChatGPT and Claude.
- [8:52](https://realalpha.app/v/DdHl7dXVt-w/?t=532) **Trust depends on software around models.** Junestrand says early products needed guardrails, citations, retrieval systems and workarounds for context windows and rate limits. As models improve, he sees Legora's role shifting toward giving them the right environment, tools and interface so lawyers can use them with trust.
- [10:51](https://realalpha.app/v/DdHl7dXVt-w/?t=651) **Engineering shaped Legora's product organization.** Junestrand says Legora built an engineering-heavy team because understanding models and creating differentiated products were central. For due diligence, three engineers built Tabular Review to process tens of thousands of documents and prompts in parallel. He says the company also held back on selling for a period while it built reliability.
- [18:03](https://realalpha.app/v/DdHl7dXVt-w/?t=1083) **AI-native teams must replace their work.** Junestrand says teams must be willing to discard software as models improve and the cost of building falls. He tells executives to keep scaling with the company and prioritize the company over their function. He says work that once required 500 engineers might now be done by 50.
- [22:00](https://realalpha.app/v/DdHl7dXVt-w/?t=1320) **Model evals turn tasks into product targets.** Junestrand says Legora keeps its roadmap short because model upgrades can change what is possible. Customers supplied tasks and evaluations; he recalls a Danish law firm use case for reviewing LPA key terms that improved from 60% accuracy to 100% in summer 2024, replacing work that took an associate three days.
- [27:23](https://realalpha.app/v/DdHl7dXVt-w/?t=1643) **Pilots let Legora prove value in practice.** Junestrand says Legora offered 30- or 60-day pilots and let firms compare products, without adding friction to how they wanted to buy. The team used legal engineers to help customers adopt the product, and he says workflows built during pilots made the product sticky; Legora also created a team to migrate customers from competitors.
- [32:52](https://realalpha.app/v/DdHl7dXVt-w/?t=1972) **Legora expanded before building regional playbooks.** Chetan recalls that Junestrand flew from San Francisco to New Delhi after learning that a major Indian firm wanted to buy, and the firm became a customer. Junestrand says his first Swedish customer introduced him to firms in other countries, and Legora served Cleary Gottlieb and Goodwin Procter from Stockholm before opening a US office.
- [36:30](https://realalpha.app/v/DdHl7dXVt-w/?t=2190) **European roots shaped Legora's product.** Chetan argues that service industries can see slow technology adoption followed by rapid uptake, and that European legal software companies must support different countries from the start. He says Legora's early prototype already supported multiple languages and legal frameworks, reflecting the need to serve markets beyond Sweden.
- [39:24](https://realalpha.app/v/DdHl7dXVt-w/?t=2364) **Stockholm culture became a global operating model.** Chetan describes Legora's early team as technically deep, intense and focused on winning, with recruitment across Europe from the start. Junestrand says international hires onboard in Stockholm and early employees moved to new offices to establish the same cadence. He recalls a Swedish saying about tasting blood after hard work that became a company-wide joke.
- [46:57](https://realalpha.app/v/DdHl7dXVt-w/?t=2817) **Legora's Series D drew $1.5 billion in demand.** Junestrand says the Series D was the first fundraise he ran with CFO David, who had joined from Vanta. He says the round was oversubscribed, with about $1.5 billion in demand, and that Excel led it with participation from Manlo and Bain.

## Transcript

Uncapped, hosted by Jack Altman and Chetan, with Max Junestrand.

Transcribed by machine (Whisper) from the episode’s audio, so a word may be off here and there.

[0:00](https://realalpha.app/v/DdHl7dXVt-w/?t=0) I remember doing this interview in Swedish. There's a saying, like, blood smock. And, you know, like, you taste the blood because you worked so hard. Yeah. She publishes the article in English. At LaGuardia, 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? 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. Well, when we open our San Francisco office, they're going to taste the blood. Yeah, they're going to taste the blood.

[0:29](https://realalpha.app/v/DdHl7dXVt-w/?t=29) I love it. Well, this is going to be a cool new format. I'm here with my new partner, Chathan and Max. And Max, you're the founder CEO of Lagora, which is an amazing legal tech company that Chathan 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 making this happen. Thank you so much, Jack. It's great to be here. Okay, so I want to start with the topic of competition. And Chathan, when you invested in the company, there were already competitors out there. This was, I think it was only two years. It's crazy because Lagorre is like two years ago.

[1:00](https://realalpha.app/v/DdHl7dXVt-w/?t=60) It's a big company already. Almost 400 people. You know, but 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, Chatham. Like what was in your head at the moment you invested? Were you thinking about the landscape around like where you just Max is so special that I don't care? Like what was going through your head when you did that? The first meeting that we had was with Max, was with me, Peter, Max, actually in the other room. And interestingly, I had invested in two other legal software companies pre-AI.

[1:35](https://realalpha.app/v/DdHl7dXVt-w/?t=95) Oh, wow. 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, 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. Or 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 there was a player in the market that had already raised at a billion dollar valuation.

[2:11](https://realalpha.app/v/DdHl7dXVt-w/?t=131) And when Max came in to chat with me and Peter, the thing that immediately jumped out was the clarity of thought that Max had on why the general foundation models had a lot of room to grow. intelligence and how that was going to be a huge boon for the legal profession over the next couple years. And so we get 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. Max, since you're here, can you like explain like what was that? So I think 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 um 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 great file uploads and like great parsing and great chunking and all of these

[3:32](https://realalpha.app/v/DdHl7dXVt-w/?t=212) things, that was where the value was. And there was another part of your experience, which was that you were actually embedded in a law firm. Yes. 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 lagora team when we invested with 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 sounds nice sounds great uh 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 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.

[4:33](https://realalpha.app/v/DdHl7dXVt-w/?t=273) 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'd often even are paying for it. Right. But that did, as Chetan 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. 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?

[5:08](https://realalpha.app/v/DdHl7dXVt-w/?t=308) And was that important to do without experts? So it's actually funny. I mean, the founding, and this is a bit of the Legora untold. First revealed here. First revealed. The company formation was in 2020. And there were four co-founders. I didn't know that. And I was not one of them. Didn't know that either. 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 SweeBERT. It was impossible to work with. Not only was it not very intelligent, it was also blatantly racist, because I've been trained on the Swedish forums.

[5:49](https://realalpha.app/v/DdHl7dXVt-w/?t=349) Some racist data there. Some racist data there. When the LLM's like 3.5 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 GPT plus the document management system.

[6:27](https://realalpha.app/v/DdHl7dXVt-w/?t=387) So basically like an LLM that could rag into the existing precedent and data that the firm was using. 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. Are you surprised by like how strongly the legal market has adopted AI? If I had thought, you know, in 2023, let's say, or 24, like what's going to 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.

[7:00](https://realalpha.app/v/DdHl7dXVt-w/?t=420) 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? Yes, it's been vivid. But second, and maybe more importantly, the law firm market is very interesting because it's like this perfect equilibrium with, frankly, like pretty low differentiation. Like if you need to do a VC deal here in the valley, like you could go to any, you know, the top five firms and you're going to get roughly the same thing.

[7:24](https://realalpha.app/v/DdHl7dXVt-w/?t=444) **Chetan Puttagunta:** 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.

[7:33](https://realalpha.app/v/DdHl7dXVt-w/?t=453) 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. that's not necessarily the same in the in-house legal sector, right? Like if one big bank says it, like another big bank doesn't necessarily need it. But was there something about the process of the way work got done or the structure? of it that allowed Lagora's product to drive so much value so fast in a way that it did force that sort of prisoner's dilemma? 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 LLMs, but they were really hard to solve like pre-LLMs. 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.

[8:30](https://realalpha.app/v/DdHl7dXVt-w/?t=510) 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 going to be playing with ChatGPT and Claude. And so if you showed up with a legal AI product, it had to be better than the foundation model. Otherwise, they were just going to say, why are you deserving of my dollars? And Microsoft Copilot rolled out very quickly. Like, every law firm in the world is a Microsoft shop. Yeah. Yeah. Like everybody works with Outlook, Microsoft Word and, you know, where they store their documents, basically.

[9:05](https://realalpha.app/v/DdHl7dXVt-w/?t=545) 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? 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.

[9:42](https://realalpha.app/v/DdHl7dXVt-w/?t=582) 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 going to transact billions of dollars of legal work on the platform. 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 open claw or claw bot or whatever it's called these days, where like with Opus 4.5 and Opus 4.6, there was an extraordinary difference in level of intelligence and like instruction following capability.

[10:23](https://realalpha.app/v/DdHl7dXVt-w/?t=623) 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 because we have to be three standard deviations ahead of any general capability yeah and that's like a very good motivator as in 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.

[11:20](https://realalpha.app/v/DdHl7dXVt-w/?t=680) 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. Yes. 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.

[12:00](https://realalpha.app/v/DdHl7dXVt-w/?t=720) But that's it. I mean, the founding team, we're 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 LangChain and these things that we initially built on, like couldn't get customized to the level that we needed back in 2024. for. 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 probably not now either. So we built this new product that we call tabular review, big matrix where you would throw in 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 lagora are xyz founders so our head of engineering jake who joined he was a solo

[13:06](https://realalpha.app/v/DdHl7dXVt-w/?t=786) founder in yc our vp product adrian was also a legal tech founder in yc and happened to be a both

[13:12](https://realalpha.app/v/DdHl7dXVt-w/?t=792) **Max Junestrand:** gc 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.

[13:21](https://realalpha.app/v/DdHl7dXVt-w/?t=801) And I also think that everything else is sort of an expression of that. Like we can only market what we actually build. 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 talk more about that period specifically basically you know the seed round you did with us was in March of 2024 the product went to GA October 1st 2024 yeah 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

[14:38](https://realalpha.app/v/DdHl7dXVt-w/?t=878) 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 yeah and we and peanuts actually those are 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. Yeah, that's right. So talk about like, well, one, you know, you calling me to tell me to come to Sweden to have that discussion.

[15:18](https://realalpha.app/v/DdHl7dXVt-w/?t=918) And you actually showing up. Yeah, I did show up. Reflecting on it, that was one of the most important things that you did in the company and the founders that in the company was at that moment, say we have 30 days to go. We're just going to sprint at these three things, not the 15 things that we could do. Yeah. Yeah. So I think there was this feeling of like, you got these LLMs, 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 15 things at the same time. And so we had to kill a few darlings and we had to like really double down on the stuff that we thought was going to work.

[16:00](https://realalpha.app/v/DdHl7dXVt-w/?t=960) We looked at on the market and we basically saw a few things that were really working like as a paradigm for LLMs 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. 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 a particular company that just had one of these features were doing more revenue than us. We were doing like 1.5 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 going to be worth to buy our suite over anybody else's. And so I wrote this very short product manifesto, send it out to the entire company and we sort of rallied the troops.

[16:59](https://realalpha.app/v/DdHl7dXVt-w/?t=1019) I think it was off the back of that that we had our first quarter where we doubled revenue.

[17:03](https://realalpha.app/v/DdHl7dXVt-w/?t=1023) **Max Junestrand:** So we went from like 1.5 to 4. We're like, oh, this is like ripping and it's flying off the shelves.

[17:10](https://realalpha.app/v/DdHl7dXVt-w/?t=1030) And then in Q1, we had another quarter where we doubled, where we went from like 4 to 8. Like, whoa, okay, now we're talking. And if it came 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 like basically agents will leverage the tools that we built so i remember early when mcp came our cto basically went well now lagora 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.

[18:16](https://realalpha.app/v/DdHl7dXVt-w/?t=1096) Chase 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 built companies pre-AI 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 yeah so I think this idea that Chetan 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 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.

[19:24](https://realalpha.app/v/DdHl7dXVt-w/?t=1164) 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 to lagora 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.

[20:12](https://realalpha.app/v/DdHl7dXVt-w/?t=1212) Totally. 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? 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.

[20:38](https://realalpha.app/v/DdHl7dXVt-w/?t=1238) **Max Junestrand:** 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

[20:52](https://realalpha.app/v/DdHl7dXVt-w/?t=1252) 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 every new point in time, I've scaled with the business. And so other people in Legora 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.

[21:28](https://realalpha.app/v/DdHl7dXVt-w/?t=1288) 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. What's nice about our work is that engineering is sort of a, 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 two things you brought up that you should it'd be great if you could dive into one is lagora 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 but it's like we have to do

[22:44](https://realalpha.app/v/DdHl7dXVt-w/?t=1364) 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 able to identify latent model capabilities that they themselves are not aware of i mean on roadmap like way back every new model just like unlocked new things right and when we got early access to gpd like 4.5 and you just realize 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 by the way to do that you need sort of like a low ego organization because you build all this ip and all this software yeah and you're like okay now the model can do it yeah delete it all worked really hard for six months yeah we're deleting everything yeah it's incredible yeah but i think a lot of the things that we have built we know that we're gonna delete someday and i guess you kind of people to opt into that at the front end for that culture to really work.

[23:51](https://realalpha.app/v/DdHl7dXVt-w/?t=1431) 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 going to 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 do you know what the next flip you're waiting for is like is there a thing 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 like dario shirt here you look like dario 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.

[24:59](https://realalpha.app/v/DdHl7dXVt-w/?t=1499) 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 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, 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.

[25:32](https://realalpha.app/v/DdHl7dXVt-w/?t=1532) I think on sort of 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 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. And we're going to call you when we can get to 100% on these evals.

[26:09](https://realalpha.app/v/DdHl7dXVt-w/?t=1569) 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 three days on basically like an associate would spend

[26:23](https://realalpha.app/v/DdHl7dXVt-w/?t=1583) **Max Junestrand:** 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 it's over i've adopted this mentality internally that if ai can do something

[26:43](https://realalpha.app/v/DdHl7dXVt-w/?t=1603) it will do it 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 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 gonna 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. 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. 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 or all of these things?

[27:59](https://realalpha.app/v/DdHl7dXVt-w/?t=1679) and then exit. The Lagora. Exit to Selva Lagora. That's a good one. How urgent is it to grow really big, really fast for Lagora, given all of the dynamics around? Chetan, 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? We can go back to sort of launch day, October 2024. so when when they launched you know roughly the error 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 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 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 was like it's cliche to say it's first principles thinking but it is because it's like

[29:16](https://realalpha.app/v/DdHl7dXVt-w/?t=1756) the team was unbiased by how to build a software company and so one of the things that you learned in sass 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 lagora is they would go put lagora into your organization and whatever you put into lagora 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.

[30:14](https://realalpha.app/v/DdHl7dXVt-w/?t=1814) They would run these competitive pilots, right? So they would say, okay, there's a couple of companies on the market. We're going to want to A, B test all of them because it's really hard to pick just, you know, based on the feature set 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 out, 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 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.

[30:57](https://realalpha.app/v/DdHl7dXVt-w/?t=1857) So we hired all these lawyers who are now called legal engineers. It's a great term, I think. Forward deployed legal engineers. I was just going to say, what about FDLE? FDLE. It'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. And I would think once you're embedded in these organizations, it's got to be sticky.

[31:32](https://realalpha.app/v/DdHl7dXVt-w/?t=1892) I think Ligore is very sticky. we've ripped out our competition at many organizations at this point. What creates stickiness?

[31:38](https://realalpha.app/v/DdHl7dXVt-w/?t=1898) **Max Junestrand:** So the stickiness is the use cases and the cadence and, you know, if you've invested time in building up a workflow that like works for you, why would you want to switch?

[31:49](https://realalpha.app/v/DdHl7dXVt-w/?t=1909) So is it that, is it? Is it, it's usage stickiness? It's not data. No, not yet. 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. So we actually have a dedicated migration team moving deployments over to Lagora. 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, just don't add friction.

[32:42](https://realalpha.app/v/DdHl7dXVt-w/?t=1962) that was actually the key on luck 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 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 because like well like one of the largest firms in india wants to buy so i figured i'd like go give it to him that's crazy and so you know this in sass it was like no like do the west regional yeah then do like the east regional yeah then do like western europe and then eventually hire an apec head and then it was like this thing yeah and because this company didn't by the way there's going to be like a year of engineering work to be even kind of ready to serve india 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

[33:54](https://realalpha.app/v/DdHl7dXVt-w/?t=2034) 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 You know what I also wonder on this? We talked about this a little bit, that like being a Europe-based company means that you are multinational from the beginning. You have to. And I think this, I'm sure some of this is pre-AI. And I think it, 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.

[34:36](https://realalpha.app/v/DdHl7dXVt-w/?t=2076) And so I'm curious if you thought about that when you invested and you're like, well, actually, maybe coming to the U.S. will be easier one day. I'm curious your experience on that. I mean, Y Combinator weren't particularly excited about backing a company in Sweden. I remember the first interview with Gustav and he's Swedish, like a Swedish partner at YC. And he goes, so you're going to move to the States, right? And I go, yes, yes, of course. That's the cue to say yes, so that you get the invite to go to YC. You're like, no, I'm good in Sweden. You guys are opening a Sweden office to YC. 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.

[35:15](https://realalpha.app/v/DdHl7dXVt-w/?t=2115) Like that was just impossible. But, you know, like the Swedish legal market is smaller than Kirkland and Ellis. So, of course, you have to expand. 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, Mannheimer 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 going to change the world and you're going to need a partner.

[35:50](https://realalpha.app/v/DdHl7dXVt-w/?t=2150) I'm here. Let's work. You know, that sort of made it all start. But then the move to the UK and the US was like when... We really started ripping. How different was coming to the U.S. versus going to Finland? Not at all. I had a rule. So there's actually a few Swedish companies that tried to go to the U.S. but did so unsuccessfully, like Klarna. They tried many times before they actually made it work.

[36:13](https://realalpha.app/v/DdHl7dXVt-w/?t=2173) **Max Junestrand:** And my rule was, if we can serve two of the biggest clients in the world, or in the U.S., from Stockholm, then we're ready.

[36:22](https://realalpha.app/v/DdHl7dXVt-w/?t=2182) And then we'll open an office here. So Cleary 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. 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.

[37:03](https://realalpha.app/v/DdHl7dXVt-w/?t=2223) 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, 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.

[37:41](https://realalpha.app/v/DdHl7dXVt-w/?t=2261) 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, Lagora sold to a Swedish firm. Yeah, that makes sense. And a Spanish firm and a Finnish firm. And so, yes, they're like laws at the European Union level. Yeah, but like from the beginning, this needs to work for many people.

[38:18](https://realalpha.app/v/DdHl7dXVt-w/?t=2298) That's right. And if you start in the U.S., 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. And different languages. 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. I remember I demoed Sweden and Spain.

[38:55](https://realalpha.app/v/DdHl7dXVt-w/?t=2335) That's right. And that was like remarkably impressive because it was a company with five people thinking global scale because they were forced to because they couldn't serve the Stockholm legal market. totally 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 it was global from day one and now i mean laguara i think has become a 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 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 when you came back from a lagora visit recently you were like oh my god they are so good like something's going on there that i haven't seen before it sounded different i don't know if it's lagora 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 it's true initially even in the I agree.

[40:00](https://realalpha.app/v/DdHl7dXVt-w/?t=2400) group of five or in that group of 10 in September of 2024, or group of 15, however big the company was, there was like 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 it's like what did it feel like to you on your recent trip there's like a few hundred people in there like yeah what did that feel like the level of engagement and buy-in 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 going to do this. It's going to be better than us at everything at some point. And they're going to, it's just going to do this. The

[41:16](https://realalpha.app/v/DdHl7dXVt-w/?t=2476) 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 we have these high bars of quality and polish. So we're going to ship fast, work really hard, build this amazing feature, and it's going to disappear within 12 weeks, requires an extreme amount of buy-in and an extreme amount of humility that we're just riding this massive wave and we don't know where it's taking us. But 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 the disadvantage of stockholm has now become lagora'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.

[42:16](https://realalpha.app/v/DdHl7dXVt-w/?t=2536) I think our competition is, you know, has remote days, like three days in office. Everybody leaves at six. Like from very early on, like we serve dinner at eight every day. A lot of people in our region are sort of tired about like all these big American winners. and we know that we have the talent and the grid and the prerequisites to build a generational company. Like, yeah, we had to go to the U.S. to raise money because we want to work with the best VCs in the world. But, like, there is a level of, like, we can also do it, right? And we have Spotify just on the street. How are you going to get this level of fervor in the U.S.?

[43:02](https://realalpha.app/v/DdHl7dXVt-w/?t=2582) I think we have. I think we have a very unique culture in our New York office. Is it different? It's very different. Well, it's not different from Stockholm. Oh, okay. We seeded it with the culture carriers from Sweden that came to New York. I think tactically, this was a really cool thing they did. Which was, I think you should tactically talk about how you make everybody interview in Stockholm. And then they have to onboard in Stockholm. Everybody onboards in Stockholm. So you live in New York, you're going to join the New York office, you're going to Stockholm. Onboard in Stockholm. People who join in Sydney have to go on a 24-hour flight to onboard in Stockholm.

[43:37](https://realalpha.app/v/DdHl7dXVt-w/?t=2617) So you can't onboard anywhere else but Stockholm. 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 to those offices to set a cadence. It was like, it's all going to be the same as Stockholm. And like the Germans who joined LaGuardia, like they have to move. Stockholm, and they'll work here a year, and then they can move back to open the German office. You have to get it right. 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 Lagora 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 dinner time, which is 8 p.m like that's when they have guests is like 8 p.m and that's been the case in every office and so that's another like thing that happened at this company and 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 onboard in stockholm yeah so you should too i mean

[44:53](https://realalpha.app/v/DdHl7dXVt-w/?t=2693) 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 totally it's also like um in some ways doing doing the u.s office in new york obviously it's not like it's an outsider city but from a tech perspective there's a lot of people in new york like i want to work at like a great tech company yeah and you know it's 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 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 Ek? 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 an outcome worth fighting for. Like then we might as well go do something else like we're only gonna play here to win you think number one number

[45:59](https://realalpha.app/v/DdHl7dXVt-w/?t=2759) two will just be vastly different outcomes oh yeah completely and it doesn't actually matter if that's the case or not but that's the way i mean gives you the right mindset yeah yeah like i think everybody's dialed into that and i mean i remember doing this interview in swedish and there's there's a saying um that you like you know like blood smock and you know like you taste the like you taste the blood and and because you worked so hard yeah and i basically told her in swedish that yeah you know sometimes i i wake up and you know it's a swedish saying and then and then she publishes the article in english yeah and the saying doesn't make any sense in english so it's like no it's like the lagora founders make wake up at lagora 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 and what how do you feel about that now Now it's become this thing, like the Americans are hashtag blood smock.

[46:57](https://realalpha.app/v/DdHl7dXVt-w/?t=2817) Like it's everybody's in on it. It's amazing. It's a cult. I mean, 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. Well, when we open our San Francisco office, they're going to taste the blood. They're going to taste the blood. All right. My last question is you just raised a big round, which is awesome. Congrats. What does this mean for the future? What's coming? Well, maybe first off, just to give you a bit of insight into the round, like every round at Legora since Chetan has been a preempted round.

[47:30](https://realalpha.app/v/DdHl7dXVt-w/?t=2850) I don't think I've ever actually gone out to fundraise since you did the round. Yeah, it's been very pleasant. We actually also have a history of taking the lowest term sheet. I remember taking, we were actually, so this is funny, Like we were negotiating the number of shares that Chetan was going to 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 going to dilute more than 17%. And we sort of look at each other and go, well, I guess we're in a bit of a stalemate here. It's like the immovable object meets the force. And so we just put on Excel, we write down the exact number of shares, and we start going decimal by decimal.

[48:15](https://realalpha.app/v/DdHl7dXVt-w/?t=2895) Wow. Until we're both. That's such, that is so legal coded. Yeah. Just the nerdy Excel. It was wild. It's perfect. So you end up investing like 9.521 and we're both equally unhappy or happy. That's great. I think we were both happy. That's a beautiful way to start. Of course. We were both happy. But the Series D has been really great because it's the first time I've done it together with someone else. So David, our CFO who just joined from Vanta, he's an absolute monster. It was funny. We had our company-wide kickoff and you get to like pick the song you want to 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 us our CFO and like the speakers just explode with this like and I don't know if you heard the song yeah yeah of course 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 CF go And I was like, that's amazing.

[49:22](https://realalpha.app/v/DdHl7dXVt-w/?t=2962) So he and I did the round. It was super fun. It was the first time we went out to actually do a fundraise. 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. That's a lot. It was crazy. But we're super thrilled about Excel coming in and leading it. Some great participation from Manlo and Bain. Well, it's awesome. It's a huge testament to what you've done and super exciting. and I think you're just getting started. So, Max, thank you for doing this. Chathan, thank you as well. And really enjoyed it. Thank you so much, Zach.