Building an AI-Native Software Company With Legora CEO Max Junestrand | Ep. 44
Max shares the story behind Legora, what it means to build truly AI-native software, and how a small Stockholm team got the world’s largest law firms to rethink how they work.
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/
Watch on YouTube; Listen on Apple Podcasts or Spotify
Clips
The untold inception story
They were working on this intersection between AI and law for three years with the early BERT models and even a Swedish trained version called SweBERT, it was impossible to work with.
Everything changed with GPT-3.5, which convinced them to go all-in on the space even before they knew the exact product.
The models are no longer the bottleneck
AI models are no longer the main limitation. The real challenge now is building the surrounding software systems that let models operate in real workflows while humans can review and trust the output.
In other words, the frontier has shifted from better models to better products that integrate those models into the real world.
No sacred cows, the models will be amazing
Founders who never built companies pre-AI have at least one big advantage: they have fewer preconceived notions about how to build a company.
This applies to how software should be built, when a product that people worked really hard on should get dissolved, what tools finance should use, how GTM should work, or really anything and everything else.
“The culture is: you don’t maximize for your function, you maximize for the company.”
Transcript
Disclaimer: Transcript generated with AI assistance and lightly edited for clarity and accuracy.
Legora’s Origin Story
Jack Altman
This is going to be a cool new format. I’m here with my new partner, Chetan, and Max. Max, you’re the founder and CEO of Legora, which is an amazing legaltech company that Chetan sits on the board of. I just feel really lucky to be doing this with both of you. Thank you for making this happen.
Max Junestrand
Thank you so much, Jack. It’s great to be here.
Jack Altman
I want to start with the topic of competition. Chetan, when you invested in the company, there were already competitors out there. This was only two years ago. It’s crazy because Legora is a big company already.
Max Junestrand
Almost 400 people.
Jack Altman
The seed was two years ago. At the time of the seed it was an early market, but there were competitors out there. I actually want to start with you, Chetan. What was in your head at the moment you invested? Were you thinking about the landscape around? Were you just thinking Max was so special that you didn’t care? What was going through your head when you did that?
Chetan Puttagunta
The first meeting that we had with Max was with me, Peter, and Max in the other room. Interestingly, I had invested in two other legal software companies, pre-AI. So there was a shape of the legal market that I intuitively understood because I participated in the market. I understood the different kinds of lawyers, who buys software, do in-house lawyers buy software, do law firms buy it… There was an intuitive understanding that I had. There’s two things that happen when you’ve sold into an industry before. Either you end up hating it or you have some strong bias against it.
There was always this idea that there’s opportunity for AI in the legal market. There was a player in the market that had already raised at a billion-dollar valuation. 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 in intelligence and how that was going to be a huge boon for the legal profession over the next couple years. He had this very strong viewpoint that there was something about legal data that the general models were going to serve in a very unique way.
Jack Altman
Max, since you’re here, can you explain what that was?
Max Junestrand
It’s worth going back to 2023 and 2024 when part of the paradigm was that you should train your own models and the general models aren’t great and fine-tuning is going to be really important. For two reasons, we were like, fuck that. One, fine-tuning doesn’t really seem to work, at least on the scale that we were operating. To train the new generational model, you had to put billions of dollars into it.
Secondly, there was so much application that you had to build on top of the models to make them useful in your environment. Back then, just solving basic data, compliance, privacy, and great file uploads and great parsing and great chunking and all of these things, that was where the value was.
Chetan Puttagunta
There was another part of your experience, which was that you were actually embedded in a law firm. So you were studying the shape of what data law firms had in a way that was… Bill talks about this a lot — does an entrepreneur strike you as a learn-it-all? It was clear that the early Legora team—when we invested it was five people—was just trying to learn everything they could about how the legal profession worked and they didn’t have any bias towards it.
The other thing Max said, which you should share with everyone, is that because they were embedded in a law firm in a windowless conference room in Stockholm—
Jack Altman
Sounds nice.
Chetan Puttagunta
Sounds great. They had a deeper understanding of the data model of a law firm in ways that most of us didn’t.
Max Junestrand
Just to take it back even further, when we started, I offered to buy a lot of lawyers lunch on LinkedIn because I wanted to learn. I would literally cold write them and say, “Hey, I’d love to meet, I’d love to talk about IP law. I’ll offer to pay you your hourly fee and lunch.” They were all too nice to make me pay for lunch, and they’re often not even paying for it. But as Chetan put it, I think it allowed us to work with customers from the very beginning. The founding team at Legora were all engineers. The first lawyer didn’t join until nine months into the journey.
Jack Altman
When you had a lawyer join, had you already set the plan and the goal for the company? Was that done without experts? Was that important to do without experts?
Max Junestrand
It’s actually funny. This is a bit of the Legora untold, first revealed here. The company formation was in 2020 and there were four co-founders.
Jack Altman
I didn’t know that.
Max Junestrand
And I was not one of them.
Jack Altman
Didn’t know that either.
Max Junestrand
They were working on this intersection between AI and law for three years with the early BERT models and even a Swedish-trained version called SweBERT. It was impossible to work with. Not only was it not very intelligent, it was also blatantly racist because it had been trained on Swedish forums.
Jack Altman
Some racist data there.
Max Junestrand
When the LLMs like 3.5 came, that was when the moment shifted. We turned this into a company. Two of the co-founders left, I joined. We basically said 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.
Funny enough, the first lawyer who joined was a soon-to-be customer of ours. He was the CIO at one of the big firms in Sweden that we wanted to sell into. He had built an early version of a GPT plus the document management system, basically an LLM that could RAG into the existing precedent and data that the firm was using. He basically said, “These guys are going to run faster than me, and if you can’t beat them, I might as well join them.” That turned out to be a good decision.
Jack Altman
Are you surprised by how strongly the legal market has adopted AI? If I had thought in 2023 or 2024 about what’s going to really adopt quickly, I don’t know if I personally would have seen it coming that lawyers would be near the top of the list. You’ve invested in stuff before too, so I guess this is for both of you. Has it been a surprise over the last two years, the rate of adoption?
Max Junestrand
Yes. It’s been vivid. But second and maybe more importantly, the law firm market is very interesting because it’s this perfect equilibrium with, frankly, pretty low differentiation. If you need to do a VC deal here in the Valley, you could go to any of the top five firms and you’re going to 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 shifts down and then everybody has to move.
What happened in the law firm market was that as soon as one big firm in a market 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. If one big bank has it, another big bank doesn’t necessarily need it.
Jack Altman
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?
Max Junestrand
I just think the legal sector was so underserved with great software for such a long time that there was a lot of built-up problems that we could easily solve with LLMs, but that were really hard to solve pre-LLMs.
Chetan Puttagunta
I also think you guys had a great insight early on, which was that there was a deference in 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 the latest software, they use the latest devices. So they were all going to be playing with ChatGPT and Claude. If you showed up with a legal AI product, it had to be better than the foundation models. Otherwise they were just going to say, “Why are you deserving of my dollars?”
Max Junestrand
Microsoft Copilot rolled out very quickly. Every law firm in the world is a Microsoft shop. Everybody works with Outlook, Microsoft Word, and where they store their documents basically.
Building an AI-Native Company
Jack Altman
To the point of you have to be better than the models, if you had to break down, as a vertical AI application, what have been the things that have allowed you to be so much better than the models that it’s worth the incremental investment?
Max Junestrand
In the beginning there were a lot of just foundational problems with the models. 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. There were a lot of rate limit issues, so you had to juggle different models for different types of tasks. There were just so many incremental, basic things to solve.
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 we’re going to transact billions of dollars of legal work on the platform. We’ve moved from building a lot of the agent work ourselves and we let the models rip a little bit more, like OpenClaw or ClawdBot or whatever it’s called these days. With Opus 4.5 and Opus 4.6, there was an extraordinary difference in level of intelligence and instruction-following capability.
So I see our job as: let’s provide the model the right environment and the right tools and skills to leverage, then let’s build a UI and an interface with the rest of the business so that they can all leverage it comfortably and with a lot of trust. I do think that the model capabilities improving so quickly makes us run faster, because we have to be three standard deviations ahead of any general capability. That’s a very good motivator.
Chetan Puttagunta
As somebody that’s invested in a lot of software companies, one of the unique things about an AI software company is that it’s tactically built differently than a traditional software company. I think it’s becoming more known now, but when you guys first started and 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. We need to deeply understand model capabilities and then bring that to our customers in a way that’s deeply differentiated. As you explained to me, that meant you needed to invest heavily in understanding the models, which then would lead to understanding what to build. But as models go better, your features may not matter in six months.
Max Junestrand
Yes.
Chetan Puttagunta
Talk about how that led to an organization that was heavily technical, heavily engineering and researcher-led. 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 a couple of leaders, but that’s it.
Max Junestrand
The founding team were three engineers. The most natural hires were where we were like, let’s grab all the smart engineers that we know from college and add them into the org. In the beginning, we had to build our own agent framework because LangChain and these things that we initially built on couldn’t get customized to the level that we needed, back in 2024.
As we understood more about the model capabilities and the problems we wanted to solve… 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. 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. It’s a big matrix where you would throw in tens of thousands of documents and throw in all the prompts, and it started running all of them in parallel. What we basically did was say, three engineers, you’re now on Tabular Review. This is your own company. Run.
Over 10% of the EPD org at Legora is ex-YC founders. Our head of engineering who joined, Jake, was a solo founder in YC. Our VP of product, Adrian, was also a legaltech founder in YC and happened to be both a GC and a lawyer. As we progressed, engineering and product have stayed at the core of who we are and what we do. I also think that everything else is an expression of that. We can only market what we actually build. We can only sell what we actually build, and product lead compounds.
As you put it in the beginning, we did not show up first. 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. If you want to be best, then you need to invest in product, you need to invest in engineering, and you need to build that culture of reliability first. We actually had a time period in the company for six months where we didn’t sell, basically, because we weren’t ready to 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 investing in that.
Chetan Puttagunta
Talk more about that period specifically. The seed round you did with us was in March of 2024. The product went to GA October 1st, 2024.
You called me early September 2024 and said I 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. We came and sat with the whole company. It was literally the whole company, which wasn’t that big back then, only 20 people. It was the whole company, the founders, chicken wings and beer.
And peanuts actually. Those were the three things served. There was a very open dialogue of, how do we get this thing out in 30 days? Because at that point, you essentially weren’t facing the market test. You were building. There were 10,000 things you could build. The outcome of that discussion was that we’re only going to focus on three use cases.
Max Junestrand
That’s right.
Chetan Puttagunta
So talk about one, you calling me to tell me to come to Sweden to have that discussion—
Max Junestrand
And you actually showing up.
Chetan Puttagunta
I did show up. Reflecting on it, that was one of the most important things that you and the founders did in the company, at that moment saying, we have 30 days to go. We’re just going to sprint at these three things, not the 15 things that we could do.
Max Junestrand
There was this feeling of: you get 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. Wrong decision. You can’t solve 15 things at the same time. We had to kill a few darlings and really double down on the stuff that we thought was going to work.
We looked at the market and basically saw a few things that were really working as a paradigm for LLMs in legal. One of them was this big tabular extraction. Another one was embedding it deeply into Word and Outlook, basically having Legora be accessible wherever the lawyer is already working. We were still called Leya back then, this was very early. We took the entire company and had a town hall. I remember showing some numbers where a particular company that just had one of these features was doing more revenue than us. We were doing 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 mostly selling to 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 it to buy our suite over anybody else’s.
I wrote this very short product manifesto, sent it out to the entire company, and we rallied the troops. It was off the back of that that we had our first quarter where we doubled revenue. We went from 1.5 to four. We were like, oh, this is ripping and it’s flying off the shelves. Then in Q1 we had another quarter where we doubled, going from four to eight. Whoa, okay, now we’re talking. It became time to launch in the US. We hired Patrick and Evan who joined from a competitor, and we had our first boots on the ground in the US. Then we felt okay, what we have is a winning formula, so we just need to crunch it out everywhere.
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 that humans are probably not going to work with all these tools. Agents will basically leverage the tools that we built. I remember when MCP came, our CTO basically went, “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.” Now we’re seeing more people basically use our agent that uses the tabular grid, or our agent who uses our word editing capabilities, than humans actually going and using those features at all.
No Sacred Cows, the Models Will Be Amazing
Jack Altman
Chetan made a cool point to me recently. We were talking about how companies that are pre AI and companies that are fully AI native just have to be built differently in various ways. Because you didn’t build a pre-AI company, I think it gives you this unshackled mind. 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?
You talked about how having YC founders inside the company has been helpful and I’m sure there’s a lot there. I’m curious, what are the main tenets that you’ve observed? Because now you’ve probably hired a lot of people who did work and built companies pre-AI. What do you think are the main tenets, ideas, and cultural concepts that have been important to you, just to make it work in a fully AI-native world?
Max Junestrand
I think this idea that Chetan brought up—you have to be willing to kill the stuff that you’ve done in the past—is very important. In more traditional software, you have to build the foundations and then you build the stuff on top of it and keep building the stack. In that world, it was also very good to have a technical architecture where one feature would rely on the same microservices as other features.
But the problem is, in AI, maybe that feature now needs to scale really quickly, and the cost of writing software is so low that it’s basically better to build your own stack for each thing. Now that we hire finance professionals or even lawyers internally to Legora—we just hired our first tax person—they come with a set of ideas. “Oh, this is how I used to do it in my old company.” Everybody’s forced to relearn, and also question what their value is on top of the general model capabilities, which was very painful.
Jack Altman
Totally. Bret Taylor talked about this on this podcast too. Basically people are going to build something and six months later we might just kill that thing and everybody needs to be comfortable with that. Historically, that would be a lot of painful internal conversations. Do you have to change? Is that a different culture for people?
Max Junestrand
I think it’s a different culture completely. The culture is that you don’t maximize for your function, you maximize for the company always. I’m very upfront with every exec who joins Legora that, in a way, you’re joining with an expiration date. You have to continuously prove that you scale out of that, because the company is scaling so exponentially. I don’t know if it was Mark Zuckerberg or somebody who talked about hiring people with high y-slopes and not high y-intercepts.
I think about that a lot, mostly because I’ve had to do that. 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. Other people at Legora need to do the same. I think that goes for every function. An engineering team that’s shipping the amount that we do, previously had to be 500 people, and now we can get away with being 50. There’s even a question of whether we need to be more than a 100 engineers, or is the bottleneck really knowing what to build and building it the right way, and designing an experience that works for hundreds of thousands of people that we now have on the platform.
The paradigm is shifting all the time. What’s nice about our work is that engineering is a roadmap of what’s going to happen in other industries too. The general models have come the furthest in coding, but also those organizations are very quick to adopt and shift. Engineering orgs are today looking slightly different, and I think we can expect the same in legal organizations.
Chetan Puttagunta
Two things you brought up that it’d be great if you could dive into. One is that Legora doesn’t really have a long-term roadmap. You guys react and build today. When you first got started, you had this nearly weekly cadence. That’s how long you would roadmap to. These days it feels like you almost roadmap on a daily cadence. Things change tomorrow. You wake up and it’s like, we have to do something different. Talk about that lack of roadmap.
Also the other thing that you’ve invested heavily in is just understanding model capability and the proprietary eval infrastructure you’ve built. You’ve had these conversations with the foundation model companies about how you’re able to identify latent model capabilities that they themselves are not aware of.
Max Junestrand
On roadmap, way back, every new model just unlocked new things. When we got early access to GPT 4.5, you just realized that holy shit, now it can finally draft an end-to-end thing and we don’t need all these harnesses and things around it. That’s amazing. Let’s unleash it in a way that works.
Chetan Puttagunta
By the way, to do that, you need a low-ego organization. Because you build all this IP and all this software—
Max Junestrand
And you just toss it.
Chetan Puttagunta
And you’re like, okay, now the model can do it. Delete it all.
Jack Altman
“You worked really hard for six months. We’re deleting everything.”
Chetan Puttagunta
It’s incredible.
Max Junestrand
But I think a lot of the things that we have built, we know that we’re going to delete someday.
Jack Altman
I guess you need people to opt into that at the front end for that culture to really work.
Max Junestrand
We’ve also talked about it like this. If we were here today and we started building for the future that’s way over there, that’s too far out. Our customers are not going to adopt that. They don’t understand it yet. So we need to take them on the journey. We need to take them on the path of being successful.
Every iteration cycle now is shorter. Back in 2023, 2024, I think it was slightly longer. You’d have a quarter or two quarters because the models weren’t moving that fast. Every upgrade was pretty incremental. But now it flipped. Opus 4.6 flipped in capabilities. So now we have to revisit a lot of the things that we built.
Jack Altman
Do you know what the next flip you’re waiting for is? Is there a thing?
Max Junestrand
It was funny, I was at the customer advisory board at Anthropic yesterday. I’m wearing my Dario shirt here.
Jack Altman
You look like Dario.
Max Junestrand
Thank you. Most of that conversation was about how 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 a trustworthy way. They’re seeing that across basically every single vertical and every single company.
I don’t really think that we’re waiting for new model capabilities anymore. There’s nice things to have. It’s nice to have better context windows, it allows us to do less garbage and context management. When you overflow the context in memory and so on, you have to deal with it to refresh it. So there’s nice-to-haves, but 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’s where all of our focus is.
On discovering what the models can do, we thought very early on that evals were going to be important, both building up an exercise of building new evals, but also building out evals for all the use cases that we want to cover. Because in the beginning it was a lot of, “how good is Sonnet? How good is Gemini? How good is GPT?” We had to test them on the different evals. A lot of our customers actually contributed to this. 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.”
I actually remember. It was a funds-related use case, an LPA key-term review report that a Danish law firm was spending three days on. Basically an associate would spend three days putting together that report. In summer of 2024, we had 60% accuracy on that task. By the end of that summer, we had 100% accuracy. Once you get to 100% accuracy, that task is done, it’s over.
I’ve adopted this mentality internally that if AI can do something, it will do it. With our product, we think a lot about solving legal tasks end to end. Once a task is conquered, it’s done. We just strike it out and we’re on this path of solving more and more complex tasks. 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.
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 doing your normal job? A lot of the organizations that we work with really struggle with keeping up with the technology uplift, even with our developments. We’re struggling by getting all the latest models and turning that into product, and they have to adopt it, and then their customers have to adopt it.
Winning Pilots and Global Expansion
Jack Altman
Here’s a question for both of you. As I’m listening to you talk, I can sort of see the hill climb that you’re on. You’ve attacked one part of it and the next one’s coming and the next one’s coming. One of the things I’m thinking about is, for a new startup in legal, what would the right strategy be for them? How do you possibly get into the mix fast enough for all of these things and then—
Max Junestrand
Exit to Legora.
Jack Altman
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 this? Chetan, I’m curious how you think about this. Is it the same urgency as always, or do any of these dynamics mean that getting to real scale is more urgent here than other places?
Chetan Puttagunta
We can go back to launch day, October 2024. When they launched, roughly the ARR of the business rounded to a million dollars. If you go back into that moment, there was this exercise of, should we make a budget? 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 we just needed to go literally as fast as we could to get the product in as many hands as we could. Because ultimately the whole theory of the company didn’t work until we got product feedback. That was literally the aim. Get this out as quickly as possible into as many hands as possible.
One of the things that Max did… It’s cliche to say it’s first-principles thinking, but it is, because the team was unbiased by how to build a software company. One of the things you learned in SaaS was the way you do pilots is you would go in, do a time-trial pilot where you would give them access to the application. 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 and whatever you put into Legora, they would leave behind even if you didn’t want it.
So there was this idea that, “Hey, you adopted AI, you did stuff with AI, you built some practices. Whatever skills you built or whatever IP you built, it’s kind of yours. We can leave that behind. It’s not a big deal. It’s your skills, it’s the things that you’ve learned.” Then Max went around and just gave people 30-day pilots, 60-day pilots, whatever they wanted. 90-day pilots.
Max Junestrand
They would run these competitive pilots. 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 based on the feature set on your website.
In those pilots, I think we did an extraordinarily good job of delivering value. When the 30 days were up, if we shut it down, it would be a riot. People would roar and they’d be like, “We’ve never seen software adoption like this in a legal organization. We need this and we need it now.”
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. We hired all these lawyers, who are now called legal engineers. It’s a great term, forward-deployed legal engineers.
Jack Altman
I was just going to say, what about FDLE?
Max Junestrand
That’s right, FDLE. They’re amazing. They’re the most tech-savvy lawyers in different organizations who don’t want to make partner, because that’s one type of life. They want to work in a tech company and now they get to work with their practice that they’re amazing at, and technology. Then they get to work with the best legal organizations in the world and drive that change.
Jack Altman
I would think once you’re embedded in these organizations, it’s got to be sticky.
Max Junestrand
I think Legora is very sticky. We’ve ripped out our competition at many organizations at this point.
Jack Altman
What creates stickiness?
Max Junestrand
The stickiness is the use cases and the cadence. If you’ve invested time in building up a workflow that works for you, why would you want to switch? It’s usage stickiness.
Jack Altman
It’s not data.
Max Junestrand
No, not yet. Not any real technical implementation, which is great, because our competition has been deployed in a lot of places with no real usage or very simple use cases. That means that we can go there, show them, and display clearly in a pilot that we deliver much better, and then we can easily swap it. So we actually have a dedicated migration team moving deployments over to Legora.
Chetan Puttagunta
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. If a customer wanted to buy a certain way, wanted to do a pilot, whatever, just don’t add friction. That was actually the key unlock. There was this idea of, let’s just go get this in everybody’s hands and not have any bias.
One of my favorite stories about Max is that he came to San Francisco to sell a bunch of clients and then he texted me and was like, “Are you free for dinner?” So we met for dinner and then he asked for a ride to the airport. I casually asked, “Where are you going?” expecting him to say Seattle or LA or something. He was like, “I’m going to New Delhi.” I was like, “Why are you going to New Delhi?” He was like, “Well, one of the largest firms in India wants to buy. So I figured I’d go give it to them.”
Jack Altman
That’s crazy.
Chetan Puttagunta
You know this. In SaaS it was like, “No, do the West regional, then do the East regional, then do Western Europe, and then eventually hire an APAC head.” It was this whole thing.
Jack Altman
And by the way, there’s going to be a year of engineering work to be even ready to serve India.
Chetan Puttagunta
100%. And because 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, one quarter into selling the product. So Max got on a flight, went to India, and a customer in India bought. It was one of those things where because they didn’t have the patterns, they were able to get big globally in parallel.
Jack Altman
I also wonder about this. We talked about this a little bit. Being a Europe-based company means that you are multinational from the beginning.
Max Junestrand
You have to be.
Jack Altman
I think some of this is pre-AI, a lot of it is. But I also think there’s a thing where if you started in Europe, you’ve already learned how to sell to ten countries. You know that there’s differences in the way the cultures work and the way they purchase software and what the rules and regulations are. I’m curious if you thought about that when you invested, that actually, maybe coming to the US will be easier one day. And I’m curious about your experience on that.
Max Junestrand
Y Combinator weren’t particularly excited about backing a company in Sweden. I remember the first interview with Gustaf—he’s a Swedish partner at YC—and he goes, “So you’re going to move to the States, right?” And I go, “Yes, of course.” That’s the cue to say yes so that you get the invite to go to YC.
Jack Altman
Now I’m going to Sweden. “You guys are opening in Sweden, YC, right?”
Max Junestrand
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 1:00 AM and 10:00 AM. That was just impossible. But the Swedish legal market is smaller than Kirkland & Ellis. So of course you have to expand. Naturally we went to Finland and then we went to Denmark. Then I was like, I think we got the hang of it. The most important thing was that the first customer we got, Mannheimer Swartling—the big firm in Sweden—their managing partner has such a good relationship with the other firms in other non-competitive countries that he would just introduce me. I would fly down and say the same thing I told him: “AI is going to change the world, you’re going to need a partner, I’m here, let’s work.”
That sort of made it all start. But then the move to the UK and the US was when we really started ripping.
Jack Altman
How different was coming to the US versus going to Finland?
Max Junestrand
I had a rule. 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 actually made it work. My rule was, if we can serve two of the biggest clients in the US from Stockholm, then we’re ready, and then we’ll open an office here.
So Cleary Gottlieb—amazing Wall Street firm—and Goodwin Procter, we served them both. We won their business in competitive pilots, and we could serve them from Sweden. 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.”
Starting in Europe
Chetan Puttagunta
One thing about the market structure of legal, that we knew about at Benchmark ahead of investing, is that legal has this unique market feature. It’s a services industry. In services industries technology adoption is slow at first and then rapid later.
If you look at any marketplace idea in a services area, the marketplaces are usually supply constrained, and then the minute supply unlocks, all of the supply comes online into the market and you become demand constrained. If you study marketplaces, especially marketplaces around services, this is something you fundamentally learn. It’s one of the rules of marketplaces.
In legal, the market structure is such that the initial adoption will be very slow and hard, but once it unlocks, it really unlocks. There’s some exponential viral coefficient that happens there. That’s one part about the legal industry that’s really interesting. 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 multi-geography and multi-rule systems from day zero. For example, Legora sold to a Swedish firm, a Spanish firm, and a Finnish firm. Yes, there are laws at the European Union level.
Jack Altman
But from the beginning, this needs to work for many people.
Chetan Puttagunta
That’s right. If you start in the US, what you end up designing is… There’s the federal legal system, there’s a state legal system, and then there’s regional. But it’s not as bifurcated as literally different countries.
Max Junestrand
And different languages.
Chetan Puttagunta
And different languages. So you build all this stuff on day zero that you don’t if you start in San Francisco. One of the interesting things that Max showed us in the prototype in the first meeting is that he had multi-language support already built and he had multi-legal-framework support already built.
Max Junestrand
I remember. I demoed Sweden and Spain.
Chetan Puttagunta
That’s right. That was remarkably impressive because it was a company with five people thinking on a global scale, because they were forced to. They couldn’t just serve the Stockholm legal market. Those two things meant that from the moment they launched the product and got a bunch of people to sign, immediately it was like, “Let’s go get the two big firms in every geography. Because we have to.”
Jack Altman
And it was global from day one.
Stockholm Culture and “Blodsmak”
Max Junestrand
Now, I think Legora has become a technology hub in Europe. People from Germany, from the Netherlands, from Spain, from Italy, they’re all moving to Stockholm, even in the winter, to come work with us.
Chetan Puttagunta
Talk about the culture part of it, which I think stands out a lot. It’s hard to describe to people what it’s like to visit the Legora office.
Jack Altman
When you came back from a Legora visit recently, you were like, “Oh my God, they are so good. Something’s going on there that I haven’t seen before.” It sounded different. I don’t know if it’s Legora-specific or if it’s something that happens in Sweden that can’t happen in America, but you were affected by it.
Chetan Puttagunta
It’s true. Initially, even in the group of five or ten or fifteen, however big the company was in September of 2024, there was a common thread amongst everybody. They were deeply technical, deeply intense, and had a desire to win. And they were thinking globally from day zero.
Because they were in Stockholm, they also decided to recruit all over Europe from day zero to bring people to the Stockholm office. What ended up happening is that you ended 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 wanting to win.
Jack Altman
So what did it feel like to you on your recent trip? There’s a few hundred people there. What did that feel like?
Chetan Puttagunta
The level of engagement and buy-in to the company mission was truly unique. I think the company has done a great job with this idea of building for the company. I really do think building an AI company is a real test in ego. You literally can’t have an ego because you have to have this idea that AI is just going to do this.
Jack Altman
AI is going to be better than us at everything at some point.
Chetan Puttagunta
It’s just going to do this. The foundation model will do this capability. I’m puzzling through this and it’s really hard, and it’s an amazing feature. 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 twelve weeks. That 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. We don’t worry about tomorrow because it’s a different world.
There’s a different type of energy, buy-in, and cadence that comes with that culture. It’s really interesting. The disadvantage of Stockholm has now become Legora’s advantage of being in Stockholm. Their talent population that they get to hire from is not just in Stockholm. It’s all over Europe and now it’s all over the world. Anybody that has that attitude is welcome to come join in Stockholm.
Max Junestrand
Our competition has remote days, three days in office, everybody leaves at six. From very early on… We serve dinner at eight, every day. A lot of people in our region are sort of tired of all these big American winners. We know that we have the talent and the grit and the prerequisites to build a generational company. Yeah, we had to go to the US to raise money because we want to work with the best VCs in the world. But there is a level of, we can also do it. We have Spotify just down the street.
Jack Altman
How are you going to get this level of fervor in the US?
Max Junestrand
I think we have. I think we have a very unique culture in our New York office.
Jack Altman
Is it different?
Max Junestrand
Very different. Well, it’s not different from Stockholm. We seeded it with the culture carriers from Sweden who came to New York, and I spent—
Chetan Puttagunta
I think tactically this was a really cool thing they did. You should talk about how you make everybody interview in Stockholm and then they have to onboard in Stockholm.
Jack Altman
Oh wow. So you live in New York, you’re going to join the New York office, and you’re going to Stockholm?
Max Junestrand
Onboarding in Stockholm. People who join in Sydney have to go on a 24-hour flight to onboard in Stockholm.
Chetan Puttagunta
You can’t onboard anywhere else but Stockholm. When they first opened the first international office, New York, and actually London too, people that were based in Stockholm moved to set a cadence. It’s all going to be the same as Stockholm.
Max Junestrand
The Germans who joined Legora have to move to Stockholm and work there for a year, and then they can move back to open the German office. You have to get it right.
Chetan Puttagunta
It’s a fascinating thing. I’ve been part of many companies that have many offices, and every office tends to take its own character. 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 dinner time, which is 8:00 PM. That’s when they have guests, 8:00 PM. That’s been the case in every office. That’s another thing that happened at this company. It’s interesting to me that it continues to scale. You can continue to onboard in Stockholm because every one of the 400 people that joined before you onboarded in Stockholm. So you should too.
Max Junestrand
The only reason we have that rule was because I did an internship at McKinsey and we’d have dinner at eight. So I was like, I guess that’s how you do this.
Jack Altman
Doing the US office in New York, obviously it’s not some outsider city. But from a tech perspective, there’s a lot of people in New York who want to work at a great tech company. There’s obviously been more there than in Stockholm, but it’s still different from San Francisco. I think you could probably bring some of that cultural thing there as a result.
Max Junestrand
Now we just opened in Houston and we’re opening in Chicago, all the big legal hubs.
Is this correct? Did you do a reference with Daniel Ek?
Chetan Puttagunta
Yes.
Max Junestrand
I think I heard this from you. You asked him about the culture at Legora and I think he said something like, “They’re pretty intense.”
We were very upfront with that, even in interviews. Not intense to the point where it’s not fun, but being number two in this space is not an outcome worth fighting for. Then we might as well go do something else. We’re only going to play here to win.
Jack Altman
You think number one and number two will just be vastly different outcomes?
Max Junestrand
Oh yeah, completely. It doesn’t actually matter if that’s the case or not—
Jack Altman
It gives you the right mindset.
Max Junestrand
Yeah. I think everybody’s dialed into that. I remember doing this interview in Swedish and there’s a saying: blodsmak. You taste the blood because you’ve worked so hard. I basically told her in Swedish that, “Yeah, sometimes I wake up and…” It’s a Swedish thing. I’m so tired… Then she publishes the article in English and the saying doesn’t make any sense in English.
Jack Altman
“Max is bloodthirsty.”
Max Junestrand
So it’s like, “At Legora we wake up with a metallic taste of blood in our mouths.” People in the company go, “Holy shit, is Max a vampire or does he just floss badly?”
Jack Altman
How do you feel about that now?
Max Junestrand
Now it’s become this thing. The Americans are #blodsmak. Everybody’s in on it. It’s amazing.
Jack Altman
I can feel the energy of it. It’s not a culture that I think would quite work in San Francisco. I don’t know if that’s something that you can do uniquely…
Max Junestrand
Well, when we open our San Francisco office, they’re going to taste the blodsmak.
Jack Altman
I love it.
The Series D
Jack Altman
My last question. You just raised a big round, which is awesome. Congrats. What does this mean for the future? What’s coming?
Max Junestrand
Maybe first off, just to give you a bit of insight into the round. Every round at Legora since Chetan has been a preempted round. I don’t think I’ve ever actually gone out to fundraise since the seed round. It’s been very pleasant.
We actually also have a history of taking the lowest term sheets. So this is funny. We were negotiating the number of shares that Chetan was going to buy, on Excel, in front of us. 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 17.5%.”
We sort of look at each other and go, I guess we’re in a bit of a stalemate. It was like the immovable object meets the unstoppable force. So we put it on Excel. We write down the exact number of shares, and we start going decimal by decimal until we’re both—
Jack Altman
Wow. That is so legal coded. Just the nerdy Excel.
Max Junestrand
It was wild. So you end up investing like 19.521%. We’re both equally unhappy, or happy. I think we’re both happy.
Chetan Puttagunta
Of course.
Max Junestrand
But the Series D has been really great because it’s the first time I’ve done it together with someone else. 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 pick the song you want to walk out to. He goes, “Max, I want ‘Monster’ by Kanye West.” And I go, “Okay dude.” The lights drop and I’m like, “I have a big surprise for you everyone. David is joining us, our CFO.” The speakers just explode with this. I don’t know if you’ve heard this song. He comes up on stage with so much energy. In the references, people refer to him as the CF-Go. 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 fundraise. We had a deck this time. It was wildly oversubscribed. I think we ended up having $1.5 billion in demand for the round.
Jack Altman
That’s a lot.
Max Junestrand
It was crazy. But we’re super thrilled about Accel coming in and leading it. Some great participation from Menlo and Bain.
Jack Altman
It’s awesome. It’s a huge testament to what you’ve done. It’s super exciting. I think you’re just getting started. Max, thank you for doing this. Chetan, thank you as well. Really enjoyed it.
Max Junestrand
Thank you so much, Jack.