Legora raises $150M Series C — YC W24 company goes from seed to Series C in 18 months with AI legal workspace

multiasset investing. They got industryleading yields. They are trusted by millions folks. And our next guest is already in the reream waiting room. Let's bring in Max Junstrand from Legora into the TVP Ultradome. Boom. Max, how are you doing? Welcome to the show. I'm great. Good to see you. How are you?

Congratulations on all the progress. Uh, introduce yourself, the company, and then give us the news. Of course. I'm Max student, CEO, co-founder of Legora. We're an AI powered workspace for lawyers. We just closed our series C. Uh, founded the business back in spring 2023. How much did you raise? How much did you raise?

John's ready. John's ready. 150 million on and you can't even [laughter] I got all of these pictures from I got all of these pictures back from the gym this morning from Stockholm. They had bought a huge inflatable unicorn. Maybe we can send you some pictures. It literally takes up half the office. Amazing.

They added it to the calendar so you can you can book it. Are are you a YC company? Yeah, we were in YC winter 2024. Winter 2024. Wow. Yeah. Winter 24. So it's 18 18 months. This must be one of the fastest growing NYC companies of all time. That's so actually in to serious. That's impressive.

So the VCs they' said we need 10% max and you're like best I can do is uh 8 8. 3. [laughter] Like how did that? Yeah. Is this round? tell you actually this one was easier to negotiate than the first one I did with Benchmark.

Um when I did the one with Benchmark, we sat down, we took an Excel, Chathan put in some numbers and I went, there's no way, dude. And he goes, I've never done a deal where I didn't get 20%. And then we started going down on the like point decimals and I think we landed on something like 18. 51%.

[laughter] It was extremely You got him to back off just a little tiny bit. It was good. It was He broke his rule for you. So, okay. So, how how are you we we've talked to a bunch of uh Yeah.

Let me give some context here because uh uh good friend of mine is a lawyer uh and and the firm he's at, he's he's on their like tech kind of advisory, I don't know, whatever whatever, you know, big law. Uh and he's been evaluating products. And about a year ago, he like was not impressed at all.

And when I saw him, uh I saw him last week and he was telling me that uh he now is seeing AI tools do um he called it like $100,000 worth of like diligence in like 10 minutes. And he was like huge wakeup call.

he was like thinking about um like he didn't he didn't even think his firm would be able to evolve to that even though he even even though and this is a big you know big firm but he uh he was like clients are going to realize like what's the game has changed like very quickly and not every law firm is going to is going to react uh quickly enough and so um yeah kind of want to get that's true yeah want wanted to get the update on like just how much has changed kind of over the last year because there's product innovation that's happening and then there's just like the models are getting better and they're both feeding into each other.

Yeah. Well, I I kind of view it like this. Here's the model capabilities, here's the product capabilities, and here's the people capabilities in terms of using those products and getting the most out of it. So, there's a huge sort of gap still to be filled in terms of what people are using the products for.

I mean back in 2024 when we were part of YC I mean Lorra was a glorified uh GPT rapper with sort of good rag good citations you know solved compliancy and and data issues but now I I think your friend is right the products have moved from being a convers conversational simple AI into something that solves much more sophisticated tasks and it looks very differently across transactional work or in litigation or in in-house work if If you take due diligence as an example, I mean it's effectively the exercise of looking through a large number of documents and understanding what is within those documents.

And I think LLMs were better at reading than writing initially, which is is quite [clears throat] an important distinction. So we came at this whole problem very much from the review angle. I think some companies I mean look, we were not the only ones who realized that legal and LLM was going to be a nice marriage.

They came at it from the thing like research angle or drafting angle which was much much harder to build a good company on in the early days. Yeah. And I think now what's happening is I mean I don't know how many apps you use on your phone. I use maybe five.

And what's happening is um the lawyers don't want to learn 20 different point solutions. We're bringing everything into one suite.

And then with things like MCP, we can actually also allow the really sophisticated law firm law firms to bring in corpus of their own bespoke tools and capabilities which I think gives a much richer environment.

I I have a very painful lesson around uh diligence which is why I care I'm very excited about this technology.

There was uh I worked on a deal uh last year, you know, before we started the show and uh we were in diligence on this company and uh there was a single document that killed the deal and the lawyers had already racked up like like a hund like a $100,000 bill before we before we before we found it.

Um, and it ultimately meant that all, you know, all all the parties uh walked away, but we were still sitting there with like this massive bill and it was just like unbelievably painful because it wasn't even complicated.

It was just the business was incredibly old and there was just this one deal that they had done like a decade ago that meant that uh that it was just like kind of dead in the water. Yeah.

I mean I mean what's what the tech allows is that you can also do a DD on the cell side before you even put the documents into the data room and you say hey let's go open it up to the other side right like it it's it's it's funny that it's called a data room right because it used to be a physical data room with a bunch of boxes you would go into that room you would open it up you would start reading all the documents then we got control F and you could start fing for different change of control clauses and then came the early versions of the sort of AI systems where actually the seed for what became Legora was founded back with the early BERT models if you if you remember those and you had to fine-tune the system to find specific provisions and now what's cool is you basically just ask the query in natural language and the system understands it.

So you can even go in there and say on a scale of 1 to 10 how much of a smoking gun is this document and the AI will just respond and provide its reasoning. So [snorts] I think in in the in the comment that you made will some law firms disappear? Absolutely.

I think law firms will go through a huge wave of consolidation frankly because they've never had tech and sort of real scalability as a weapon and I mean you have the big four in auditing and tech has been very good for auditing it's very good with number it's very good in finance tech has never been good at language until large language models and so now I think you'll see increasingly firms leverage these things to not only sort of outd deliver their competitors but also to outpric them you Yeah.

So is the is the solution for law firms do you think transitioning to kind of value based pricing flat flat you know more like project fees because uh you know if you compare this to like the creative world like the best logo designer in the world is not going to charge an hourly rate because they might be able to make that logo in like 30 minutes, right?

And so if they charge like you can't charge like a $100,000 hourly rate, but companies will pay $100,000 for a great logo. So is that which is correct? Uh I I I think that's correct for a lot of work. I don't think it's correct for all the work. So I'll give you an example.

When we negotiated uh this term sheet, uh we were working with Goodwin and our f and our partner Craig there. And when I need his expertise to help me negotiate the term sheet, he's worth a lot more than his hourly rate, which is I mean arguably already high, but it's worth a lot more than that in that specific case.

But when his team is reviewing simple documents, maybe that's not worth as much if AI can do that. So I almost view it as if AI can do a specific piece of task, it will do it. The only question is like where does that get transacted?

And I think you'll see um value based pricing in taking a portion of the deals that like the best law firm in the world arguably is WCTEL and they don't do hourly rates at all. They just say this is the price to win and you pay them, right? And they get a portion of that.

But I'm also actually seeing another way where um really big companies like the big tech companies are going to law firms and saying, "Hey, we're going to pay you $200 million over the next two years and we want you to do all of this work. Can you do it?

" [clears throat] And the law firm is then forced to say, "Are we going to turn down $200 million or are we going to figure out a way to do that? " And of course, then tech will be part of that answer.

So I I actually yeah it's about creating the right incentive to adopt the tech versus like currently some firms are going to resist it and being like I actually like doing diligence the oldfashioned way where we could get three people to spend you know all these hours. Uh this was super fun.

I'm super excited for you guys. I have a feeling we'll have you on a lot more in the near future. Just remarkable progress. Wish we wish we had more wish we had more time but I love to see a YC company winning and I rarely see one winning this hard. This is incredible.

And especially I got to give a shout out like we since we started in Europe, we just launched in the US back in March. So since then we've killed the team to almost 50 people and it's like the growth that's coming in the US is frankly what we're doing now. Congratulations. Thank you so much guys. Thank you so much.

We'll talk to you soon. Have a good one.