00:38:48 · Molly O'Shea, Marc Bhargava
[00:38:48] S1: of General Catalyst's very large platform that you have, how do the private market investments help determine or inform these companies? Are you partnering with any of them for them? How do... What... Like, how does, like, Anthropic fit in here, and what are you learning from them? [00:39:06] S0: Yeah. So with Anthropic, we're kinda learning where are the models going. So, you know, there's always a new release every three months, six months. We're better understanding what are the tasks that these models can do, especially as logic and reasoning is better. And then we have portfolio companies like Rox, which is taking on Salesforce, for example, and it's more AI native, or Eudia, which is focused on the legal space, also more AI native, Serval, which came out of Stealth last week, which is taking on ServiceNow in a more AI enabled way. So we're working closely with Percepta to let them know about the companies in the portfolio, what they're seeing both in terms of model improvements and also product improvements. And then Percepta is getting this real life view of, you know, everything going on as much as it can in AI and then is able to help its Fortune 100 clients implement all this new technology, a lot of which our team is helping, you know, identify and pass up to them. [00:39:56] S1: This was a good question from Kyle Harrison, but he wanted to ask, how do you decide when to choose from building an AI roll up or investing in another SaaS company?
00:40:07 · Marc Bhargava
[00:40:07] S0: Yeah. It's a really good question. One answer to that is percent automation. So if we think a space is gonna be 90 or a 100% automated, then probably software is the best solution. And honestly, an incumbent like Microsoft or Amazon or Google that has the distribution can just push the software. It can be part of your Google workplace or your Prime subscription. So if something is a 100% automatable, it probably should be a software or agentic solution. And then most likely, the winner there could be a fast growing company, but also is very likely someone who just already has the distribution. So if coding gets fully automated, maybe it can just be pushed through by Google or Microsoft or someone else. So one thing we're careful about in the AI enabled roll ups is we we target 30% automation at least, but we actually don't want more than 70% automation. Because if something is approaching 80, 90, or a 100% automation, then there's really not the people services part of it. So that's one important part. The second thing is fragmentation. Like, when the industry is really hard to sell into, imagine creating AI native software for homeowner association, HOA management. Like, that's just extremely hard to sell into. So you could create an amazing product, I'm sure, but your sales process would be very, very slow. So the second thing we look for is, hey, it's very fragmented, and it's hard to sell in a SaaS product to these businesses. And then the third thing we look for is it has to be really sticky. Like with HOA management, it's a two year contract. So it's important that, you know, it's a low churn business where we can go in, we can do all this AI implementation, and there will be some hiccups along the way, but we can kinda smooth those over and we have these kind of loyal clients. Accounting is another really good space where there's very low churn that we're in, or insurance, or MSPs. And so those are the things we look for. We do think that software services will win out in areas that are, you know, more than 80 automatable or it's easy to sell into your client base. You have a few large tech customers. There are plenty of areas where it really makes sense to be more of a software solution. That said, we think there's also this really big market for AI enabled roll ups, especially in things like services.
00:42:08 · Molly O'Shea
[00:42:08] S1: Well, to shift a little bit, Sourcery sponsored by Brex. Amazing. We love Brex. They're all about spending smarter, moving faster, and performance. And when you're working and you're building on these companies, what are the metrics that you use to determine their performance? I would assume some of it's a little abstract because it's like team and that sort of thing. But how do you measure performance?
00:42:31 · Marc Bhargava
[00:42:31] S0: Yeah. And the first tranche of funding, what we're targeting is this 30% automation. So go out and get 10 clients or get five private clients, but really show us the software you can build or the agentic workforce you can build, and then come back to us and map out, if you look at all the man hours in a company, our 30% could you automate with the products that you have built or stitched together. And so that's the first really key metric. Then the second key metric is when we go and actually buy companies, we're looking for how are you improving the margin? So you've automated 30% or more. How's that flowing through to margin? And we want a really detailed plan of how to double your EBITDA margin, generally from the 15 to 20 range to 30 to 40%. So that's kind of the second really key metric. Once you start showing us you're there or you're on track to get there, that's the second really important metric. And then the third is now you're growing and you're scaling and you're moving quickly. Well, what multiples are you buying these businesses at? And how quickly do you get those multiples down as you improve the margin profile and the EBITDA profile as well? And so then we get a bit more sensitive to entry multiples and doing things like smaller tuck in acquisitions and using debt. And then the final one is just dilution. Like, we want the founders of these companies to still own at least 10% of their business. When they go public, ideally 20 or even 30. And so, you know, that's also a really important metric. Are you compounding now with your own free cash flow and with debt financing towards the later rounds so that you can still own a big chunk of your company when you go public? And, of course, we at GC can own a big chunk ideally also 20 to 25% when these companies go public. So a really large concentrated position and things that we think can be really massive outcomes. So along the way, we have these different metrics sort of for each stage of the AI enabled roll up.
00:44:10 · Molly O'Shea, Marc Bhargava
[00:44:10] S1: Oh, wow. That's highly concentrated. [00:44:12] S0: Yeah. For sure. [00:44:14] S1: This is a really difficult question. Yeah. Where are these businesses located? Where have you traveled to?
00:44:20 · Marc Bhargava
[00:44:20] S0: Right. Well, the holding companies that we help incubate and fund are pretty much exclusively in San Francisco and New York. So out of the, you know, eight or nine deals that we've done, I think six are here, and two or three are in New York. So we have seen that talent has come back for sure to the Bay Area. It's like the center of applied AI, research AI, and then New York too for financial services especially, and some of the really great m and a specialists or people who have built and sold companies are out there. So we're primarily working with really experienced entrepreneurs, second time founders, amazing operators, and they tend to be between SF and New York. Then the companies, once we create the holdcos and then create the software, we show the automation, now we're actually buying businesses. Those are almost never in San Francisco or New York. They're all across the country. Increasingly, it's getting more global. We invested two rounds in a company called Dwelly, which is out in London, which is rolling up property management and scaling really well and also doubling the EBITDA margin of the property managers they're buying. And we've also done a deal in Germany in the accounting space. And so increasingly now, well, my answer was at first US. We also have bets in, like, UK and Germany, and we're looking at this strategy really closely in India too. And Europe has much lower entry multiples. People sometimes rat on Europe that it's hard to build a big company because there's so many markets. In some ways, the AI enabled roll up is really perfect for that because we can buy our way into new markets and iterate, and it's the same back end technology to automate accounting, for example. And so increasingly, this will be a more global strategy. But to date, it's been New York, SF, London, and Berlin.