00:07:30 · Molly O'Shea
[00:07:30] S1: Wow. I think I think what'd be really interesting would be to take a step back because General Catalyst really leaned into this moment. People have forgotten about this, but there was an existential moment for SaaS in, like, early twenty twenty three or something like that. And everyone thought venture was dead. SaaS was dead. It was the end of everything. No more venture capital. It's over. That was the that was the whole idea. But then some people thought, oh, no. This is an opportunity. This is an opportunity to roll up companies, to apply AI, to use these And one of those people or one of those funds was General Catalyst. And so you guys actually, like, really leaned in hard for this. What was the decision making process for it?
00:08:16 · Marc Bhargava
[00:08:16] S0: Yeah. For us, it was a boat strategy. So we actually think three approaches can win. One, some folks view it as the model companies will end up being the winners. They're gonna keep iterating. They make better and better models. They'll go direct to the consumer. And we're obviously investors in Anthropic, large investors from the last round, from this current round. We absolutely think companies like Anthropic and OpenAI and Google can benefit, and the model layer can benefit. So we agree with that. We also agree with folks who say, well, it's been overestimated. SaaS is not dead. If you look at public market comps, they've continued to grow, do well. There are all kinds of new, interesting SaaS companies that are being started and growing. But we also think there is this third bucket. So we're kind of an all of the above. We think there'll be winners in each category, and we obviously wanna be part of them. But that third bucket is for really fragmented industries where it's very hard to sell into AI native services and products. Can we actually build the AI native service platform and software and then go buy our distribution? So a few examples. One that was very early on was Crescendo, where we led several rounds of funding to build AI native software for call centers. And we teamed up Andy Lee, who ran Alorica for over thirty years, a call center chain with two amazing CTOs. Someone from GC went and joined full time, and we built out this software that automates 50 to 70% now of what a call center does. So after proving that out in a year and having 10 or so pilot clients, we gave them the money to actually go buy a call center. And they're well on their way now of taking 10% EBITDA margins and turning them into 40% EBITDA margins. And that's because when half the tasks can be automated, people can start to focus on cross selling, revenue opportunities, and the harder tasks. So Crescendo is just one example. With Long Lake, a second example, they've gone after the HOA management space and PEO services and others. And they are also scaling quickly, doubling the EBITDA margins of the companies they've been buying. And they have the benefit of having all of the data and the ability to do change management and change practices.
00:10:11 · Marc Bhargava, Molly O'Shea
And then, of course, you know, third and fourth, we have companies like Titan MSP and the MSP space then went out, got six pilot clients, showed us they could automate 38% of what MSP does, which is an outsourced IT services firm. And now they've bought RFA, which is a well known MSP in New York, and they also are well on their way to kind of doubling EBITDA margins. And so we definitely think that there's an opportunity for software, but there are a lot of industries that are highly fragmented. They're split across the country. They don't really buy technology products. When they do buy tech products, they call it IT, and they cap it at two or 3% of revenue. And at the same time, there's this ability with AI to go in and automate 20, 30, even 50% of the tasks at those businesses. So to really make the most out of AI technology, you wanna buy of these companies and be able to free up people to perform the higher earning tasks and really grow the company and grow the margin story. And that's what we're starting to see proven out across all of these case studies and examples, and we've been getting a lot of interest from crossover funds and others as we've been doing this, and we've really been proving the model. [00:11:13] S1: Sourcery is brought to you by Brex, the financial stack trusted by more than 30,000 companies, including one in
00:11:13 · Molly O'Shea, Molly O'Shea
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00:12:07 · Molly O'Shea
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00:14:33 · Molly O'Shea, Molly O'Shea
Full disclosures in the description. [00:14:36] S1: So these are traditionally not sexy industries at all. Definitely not. Yeah. They're very boring. They're boring. Definitely. But you came from a really fun industry. You came from crypto and everything. Right. And from my understanding and research, you looked at 70 different industries, and you landed on 10 of them for this fund. Right. What was your process for that, and how did you evaluate the opportunity set for those 10 industries?