A Product Market Fit Show | Startup Podcast for Founders
00:06:50 · Pablo Srugo, Nick Fleisher
[00:06:50] S1: Well, we're going to talk at the end about kind of two tactical deep dives. And one of them is related to this because you're hosting like two to three dinners every single week with people that could be your customers. And you've got a whole kind of playbook for that. So we're going to talk about that. We're also going to talk about why you're hiring an AE so early. Most people do it well after a millionaire. You did much earlier. So we'll talk about that as well. But let's go through now the story. Right. So what was the first idea for Sandstone? When did that happen? [00:07:15] S0: Yeah. So I was at originally engineer, built mobile apps, ended up at McKinsey. At McKinsey, all of my work happened to be legal tech. It was just very random. My first client was the biggest legal tech and research company. [00:07:29] S1: When was this, by the way? What year?
00:07:30 · Nick Fleisher
[00:07:30] S0: This was five years ago. Okay. This is pre-Gen AI. But legal started to have this moment where there was a lot more automation. And people were starting to say, we need to get our data in order. So we took this work with legal tech companies. And we started going to law firms and in-house legal teams and saying, your data is a mess. It's all over the place. You don't have any tech people within the org. Let's just go figure that out. And it was very nicely timed because then Gen AI became a thing. And all these law firms and big, massive legal departments were like, hey, we want our AI to work better. But our data is a mess. And so we pivoted into becoming sort of like a Gen AI consultancy for big law firms and legal departments. That was most of my work. But another chunk of it was actually helping McKinsey's legal team. And so McKinsey's legal team is a couple hundred lawyers. We would work with them and think about what they were doing and how it could relate to what our clients are doing. At McKinsey, if I needed a statement of work for a new client, I would message my favorite lawyer that I knew very well on Slack. She would take a couple of days to respond because she's a busy person. She would then forward it to the right person, usually through Slack or through email. And then 10 days later, that person would come back to me with a bunch of questions. After I answered those questions, a couple of days later, they would draft the statement of work and send it over to me. And so it was like this multi-week process to create something that was like, to one, connect to the right person, to two, gather the right context, and three, like create a pretty simple work product. But what I realized in that was like, most of the work was not in creating the work product, right? Which is where you think of like all the J&I applications. It was just like all the stuff before it. And so that's where the first idea was born, which was my co-founder, Jared, who's also at McKinsey. He's a lawyer. And we sort of said, why can't we just build a tool on top of Slack and Teams and email that can do that first back and forth, connect you to the right person, gather the context, and then just put it on their plate with ready to go work on the work product. And so that was, you know, V1.
00:09:29 · Nick Fleisher, Pablo Srugo
It was centralizing intake across all these different sources, finding the right lawyer in the legal department to work on it, and asking questions using AI with the business user to gather all the context before it hits the lawyer's plate. And like, we realized that was quite an unmet need. Like there were some intake point solutions, but none that were using Gen AI like that. And so we started rolling that out, you know, on the side with some of our friends. [00:09:54] S1: This is what year at this point, like when you actually decide that you want to build a solution for this? [00:09:59] S0: This is early last year. So 2025, early 2025. And over the summer, we're still at McKinsey. So call this May, June into July of last year. We were testing it on the side with our friends. And McKinsey Legal can come at me and be mad about that. But we had a lot of friends who were lawyers. And so we would ask them, hey, could you like implement this on your smaller legal team within a broader legal department and just see how it goes? There were two really interesting things that happened. One, like people started using it to just track and manage work. And we realized like legal teams never really had their version of Jira or Linear. [00:10:37] S1: Crazy. Like they don't have a CRM?
00:10:37 · Pablo Srugo, Nick Fleisher
[00:10:37] S1: Crazy. Like they don't have a CRM? [00:10:39] S0: No. So the first part was, okay, this is becoming from intake to like managing work. What we then realized is, to the point you just raised, they don't have a CRM and they don't have a single place to just manage all the context behind what's been going on. And so it expanded from just doing intake to actually the data that we have in Slack and Teams, Drive, SharePoint, all these places were integrated, is super rich for the legal team to be able to get the context on anything they're working on. So we went from just saying, let's do intake and work management to actually we're just a context engine or a CRM for the legal department. So when that request hits my desk and it's a sales agreement I need to review, we know everything about the counterparty, we can tell you who worked on the last negotiation, how it went, and we can then use that to help you answer the questions or review the new contract. And that's where the tool started to evolve from like intake front door to a real legal context engine, which is where clients are starting to get, you know, are getting more value today. [00:11:38] S1: You might not have an answer, but do you have a sense of why? Like there's plumbing businesses that have CRMs, right? Like how come a legal massive, massive business worldwide wouldn't have like a tailor-made CRM or even like a Jira-like, you know, internal kind of collaboration platform?
00:11:55 · Nick Fleisher
[00:11:55] S0: Some law firms use like Salesforce and CRMs, not very successfully. And I think part of that on the law firm side is because you also have, and it was similar to McKinsey, you have partners who kind of run their own businesses. And so to get them all bought in on like this one shared unified instance is like really hard. On the corporate legal side, like where we work, which is like we only work with in-house legal departments, right? The Fortune 500s all the way down to legal teams that are two or three people. The problem there is they're just takers of the software of the rest of the business. Like historically, like a legal department is like this back office function. It's already a big cost. Why would we give them their own hub for managing work? In the early 2000s into like 2010s, like a market did get created or grew pretty significantly, which is contract lifecycle management. And I would think of this as like V1 of the legal CRM, which was, here's a place that the legal department has that is not part of the rest of the company. And it's where they store and manage their contracts. The problem with that is twofold. One is it's only looking at contracts, right? Legal teams do a lot more than contracts. Like they answer complicated questions. They work on HR matters. They work on many different things. And two, it's very point in time. So it's just looking at contracts that are like executed and signed versus like what are all the communications and processes that we're doing that lead up to that, right? So it's not actually the most helpful resource for AI because we're only looking at a snapshot of the data of the legal department. And so we kind of think of like what we're building now, this legal relationship management tool as like the second wave of contract lifecycle management.
00:13:32 · Pablo Srugo
[00:13:32] S1: Why do you focus only on in-house?