Sandstone AI raises $30M Series A led by Lightspeed, grows 40x in 150 days serving Fortune 500 legal teams

Speaker 1: That's fantastic. Let me tell you about Shopify. Shopify is the commerce platform that grows with your business and lets you sell in seconds online, in store, on mobile, on social, on marketplaces, and now with AI agents. And our next guest is already in the waiting room. We have Nick Fleisher returning to the TV from

Speaker 12: Sandstone. He's the cofounder and CEO. How are doing, Nick? Good to see you. Great. Great to be back. Great to be back. How are you guys? Great to see you. We're doing great. Overnight success. What's going on? You raised some more money? Tell us about it. We we we raised some more money. Today, we announced a $30,000,000 series a led by Lightspeed.

Speaker 2: Nice. There we go. You're moving at Lightspeed.

Speaker 1: Tell us what's going on. What's the traction? What's what's the unlock? What's the actual product doing for people day to day?

Speaker 12: Yeah. The the product is legal relationship management, which means we centralize intake and knowledge for in house legal teams so that they can actually, deploy it in AI workflows that that are useful. Since we launched about a hundred and fifty days ago, we've deployed to, you know, dozens of Fortune 500s and mid market companies across industries like manufacturing, commerce, tech, and we've grown the business by 40 x. The team has tripled since we last spoke end of January, and we're excited about bringing this this tech to legal teams who are really in need. You know, we we like to say that we are playing against a legacy market, which is called contract life cycle management. Very boring tools where in house teams historically store contracts, and that's about it. And they are, you know, burdened and gated by that piece of tech, and we wanna help unlock them so they can actually, you know, use use the great AI that's out there now. K. Your investors haven't exactly sat out the foundation model race. There's been a lot of thud around rappers

Speaker 1: and application layer companies, all sorts of derogatory terms thrown around. At the same time, we just saw data from Cursor, Cognition, a couple other firms that appear to be in the direct path of the AI labs. They're all growing. They're accelerating. They're doing great. How did you frame that question during this round of pitches?

Speaker 12: Yeah. And I mean, Claude is, you know, Claude has announced Claude for legal. OpenAI made a big hire Yeah. Last week in the in the legal tech space. And so they're they definitely want to play and I think most of where we see them playing is on quick legal questions, legal research, and redlining of documents. Yeah. And we explicitly said from the start, we think redlining and marking up documents is gonna be commoditized by the by the labs. Interesting. And so we said we wanna actually build a workflow tool that's helpful for in house teams. And so, you know, even the most forward thinking tech companies are paying us, one, for opinions on what those workflows should look like and how to implement them. Two, the context layer to actually think about, you know, how does each legal decision and relationship map, you know, to everything else, and how do we, you know, retrieve that at the right moment so that we're pulling the proper context when I'm answering a question or looking at a document. And then I think the final one is, you know, building a tool that learns from your past legal decisions and can work for not just the stakeholders within your legal team, but also the the folks in the business who are requesting work from legal, that's a lot more complex than any, you know, chatbot or or self built tool is gonna is gonna be able to do. Yeah. Has

Speaker 2: token maxing hit the the legal community in any way? Interesting. I would assume no because there's maybe a more like finite amount of like companies aren't, you know, a software company wakes up in the morning and there's like, there's so much software to build. We wanna build as many individual features as we can. You know, there's stuff to build internally and externally and all these things. Whereas like an in house legal team

Speaker 1: is not necessarily waking up and being like, we want a 100 x the amount tech company might go back and say, review every line of code in our code base for bugs.

Speaker 12: A law firm probably isn't going back and saying like, review every document we've ever sent and do another red line on it when our client's not paying us. Sure. But what how how have you been interpreting it? The token maxing question. I I think I think generally, we we don't see that happening. We don't see it happening at scale, but you could see it in a world where people say, hey, can you redline this or review this agreement or answer this question in the 50 different ways that is that, you know, we potentially could and see how it plays out in a negotiation. Right? Can we simulate what the outcome could be here? And so I think we see some people playing with the idea of, you know, using AI to do things that are maybe outside of the the day to day. But, you know, I had a GC the other day on a demo tell me we are definitely not AI maxing today, and we won't be doing it soon. And I think they are much more cautious, and historically, is seen as a cost center and a bottleneck. I think that's going to change a lot over the next couple months, but they are the last ones to get the, you know, ridiculous token limits and and ability to go do those experiments.

Speaker 2: Yeah. That makes sense.

Speaker 1: Much effort are you putting into, like, harness development specifically these days? It feels like that was the unexpected win of the last, like, six months across Clog Code, Codex, Cognition, what they're doing. Like, people at least a year ago or two years ago thought, like, the model will be everything. Everything's gonna be in the model. You're not going to like this whole prompt engineering thing sort of evolved into harness engineering and it's born fruit for so many firms. Are you focused on that?

Speaker 12: Yeah. I mean, one of the things that we'll do with clients is we'll say, hey, take all the integrations that we have that you have connected through Sandstone and connect them with MCP and to Cloud and OpenAI and and just see what, one, the quality is of the, you know, ability for it to retrieve context and answer your questions, and two, the the cost because you're not necessarily routing to the the right model for the given task. And so, you know, if you do that experiment, you're gonna see that, you know, 50 x the results on on the Sandstone side, and that that happens with nearly every legal request that hits a a legal team within a company. And so a lot of it is around how do we map data and context from other systems and actually go retrieve that, you know, when these questions are being asked or when we're reviewing documents. And then a lot of it is also just the,

Speaker 1: you know, underlying decisions around what models to be using when. Typical path in law, at least from my understanding, is usually like law school takes forever, a couple years at a corporate law firm, then you can make the jump to in house counsel somewhere. Yeah. Is AI going to lower the age requirement, the experience requirement for in house counsels? Like, should should will we should we expect to see 10 person start up, 20 person start up say, yeah, let's get someone who just graduated. They passed the bar. They're a lawyer. But instead of them spending five years at a white shoe law firm, let's have them jump over because we know they're going be super powered? Or how does the dynamic play out on that side?

Speaker 12: Potentially, I I think we will see some of that. The two the two pushbacks I would have are one, you you wanna hire a GC or an in house lawyer who has experience dealing with different types of counterparties so they can actually, you know, go up and have the negotiation and and, you know, have a good backing and background when they come to those conversations. And I think, two, you still gain a lot from sort of the hustle and the grind of all of the work that you do in big law. Yeah. That will decrease a little bit, but I don't think it'll go away completely in the next five years. I do think we're going to see more non lawyers on in house legal teams. Like, we have some clients who have hired engineers fully to their legal teams, and historically, has had this role called legal ops, which is essentially, you know, if you think about rev ops on the the revenue side, it is sort of the person who, you know, pulls everything together, the systems, manages the processes. These people are becoming more and more technical, and I think we're just going to see a lot more of them. Like, know, you look at Mercury's legal team, I think it's in the, you know, 20 to 30 person legal team range and, you know, they have several people doing legal ops. Historically, it would have been maybe one or, you know, at most two for a 30 person legal team. But we see people focusing on it more and more. That's very cool. Are you tracking on the on the consumer

Speaker 1: legal side? Like legal Zoom, this is sort of out of your wheelhouse, but I'm just sort of interested Yeah. Well, it's more more interesting to ask you than Yeah. Somebody that's actually building an space. Legal Zoom was like so magical. Initially, was form filling and then we got Stripe Atlas. But is there more there? I mean, people are going to go to the models and demand legal advice one way or another. Jailbreak them if they have to. But how does that market change? How do you think what do you think is gonna happen in that market? Is there anything interesting you see as changing? There's

Speaker 12: so much opportunity. Right? Like, those tools are historically very much just mapping you to the right person who can do the services, and it should all get disrupted, and there's very little investment and focus there. So like, if I was starting another company today, like, that's a really great market, and I think it's very specialized, right? You see some popping up on the consumer, divorce and family law side, and we'll see that in all the different areas. The the other thing is just law is getting more complex, and there's a lot more of it because of AI. Right? All of our clients are telling us they're busier than ever because, you know, the people in the business are negotiating more. They're doing things with AI that they shouldn't be. They're creating more text and more words. Right? The business users are token maxing. Yeah. And so as a result, there's just more legal work. Right? And there's more regulation. And so you're gonna see people wanting cheaper options for, getting the answers to their questions and getting through cases. Yeah. Tyler Cowen had a funny take on this. There was like, even in the most aggressive ASI scenario,

Speaker 1: you're going to have tons and tons of government lawyers because we're going to want the humans to write the laws that govern the AI and whatnot. Anyway, thank you so much for taking the time to come chat with me. Fantastic progress. Congrats on the 40 x to the whole team. We're going to hold you to that the next time you come on. Better be a 40 x. Ideally, ideally accelerate. Yeah. Yeah. Maybe 400 x in a hundred and fifty days. There we go. Just call him the shot. Call him the shot. Love it. Have a great rest of We'll talk to you soon. And I'll tell everyone about MongoDB. What's the only thing faster than the market? Your business on MongoDB,

Speaker 2: don't just build AI, own the data platform that powers John. Yes. Did you know that Dwarkesh Patel's assistant is the brother of Leopold's fiance's boss?

Speaker 1: I heard that I heard that Dwarkish Patel's hairstylist's uncle went to school with Demis at DeepMind in preschool. And so I thought that was something that needed to be disclosed.

Speaker 2: I think you're thinking of it as the preschool teacher. The preschool teacher. That's right. Okay. Well, yeah.

Speaker 1: News flash, Silicon Valley is small place. And in fact, this is so funny because it's like, actually all the people in AI live in the same house. That's Yeah. That that's the real story here. It's not that there's some crazy It's assistant is the brother of the boss.

Speaker 2: A small And you're not in it. Anyway,

Speaker 1: it's very funny that somebody tried to drop this as a bombshell Yeah. And and wound up writing one of the most confusing lines on No, it's not in. We're still creating new sentence structures. We are. We are. Never before in the English language is something so confusing. Before Before we bring in our next guest, Chris, Ninja Wan. We have

Speaker 2: Paul Graham said What did say? I strive to make my writing unsummarizable in the sense that it has so little fluff left in it If you take any words out as summaries by definition do, you lose a lot of interesting ideas. And so he says, well

Speaker 1: And they quit. Why is this block three d? Blocked out the rest of the text. But why is it three d with a beautiful light gradient rip like flourishing off of it? Like, I don't understand the the like, you could have just gone into iOS, put a little black box over this or blur it or something. They chose to put a three d block there that's I like with a blue light and a white light on the right. It looks very aesthetic. This feels But Paul Graham fires back and says, are you trying to prove my point or just doing it accidentally? If I'd written just that, no one would have understood what I meant. The only reason people can understand your version is that they can also see the original. Owned. I wonder I wonder is I strive to make my writing unsummarizable a banger? Do you think that one gets more posts, more likes? They originally got 5.2 k likes. Do you think I strive to make my writing unsummarizable