00:09:09 · Gil Feig, Molly O'Shea, Shensi Ding
[00:09:09] S0: Yeah, the only, we just have security reviews, obviously. Can have people going wild on every tool, but otherwise, yeah. [00:09:14] S1: Yeah. So let's talk about the growth. So what are the current metrics of the company? How many customers do you have now? [00:09:22] S2: Yes. So we have over, I think over like 20,000 self serve organizations on the platform, might be 25 now, I probably need to check, and over 400 enterprise customers on the platform too. [00:09:32] S1: I think Brex is one of your customers. [00:09:34] S2: They are. We love Brex. [00:09:36] S0: They're good customer [00:09:36] S2: of Michael Tanenbaum, actually helped bring us in, like, a long time ago. [00:09:40] S1: Oh my gosh. I know. [00:09:42] S2: I know. I love him. I really love him. Yeah. He's, yeah, he's like the GOAT. [00:09:46] S1: What are the main categories of customers that you bring in and what are their use cases? [00:09:52] S2: Yeah. So there's a couple different categories like traditional SaaS platforms, which can include something like AI. So like our first customer ever was Drata. And then we, of course, sell to [00:10:00] S1: lot of [00:10:00] S2: the SOC two platforms like Drata, Vanta, [00:10:03] S0: Sprintero. [00:10:03] S2: Yeah. You name it. Then also No. You know, sadly, they didn't sadly, they didn't onboard onto George. [00:10:11] S0: Next topic on this one. And then
00:10:11 · Gil Feig, Shensi Ding, Molly O'Shea
[00:10:11] S0: Next topic on this one. And then [00:10:14] S2: expense management platforms. So, yeah, like Brax, Ramp, and like a few I have a few others as well. And then also large financial services. We have customers like JPMorgan, US Bank. Yeah. And that's been really awesome for us. Then of course, like the large AI companies, and that's been like a newer segment that we actively invested in early last year. So we do serve some of the largest AI companies in the world powering their AI search functionality and also connectivity in their products. [00:10:38] S0: Yeah, that would be large LLMs as well as some of the largest, you know, AI, I'm not going to say wrapper, but you know, AI SaaS ish platforms. [00:10:45] S1: Yeah. What is the difference in selling to these different because that's a lot of different categories there and also stages of company. [00:10:52] S2: The types of products that they're probably purchasing defer a little bit. And so we're able to, we're able to have a, like, a guess on, like, what what products they'll be mostly interested in. So for, large financial services, usually, it's probably, like, our unified API for deterministic use cases. Or if they're building some kind of, like, agentic product, then they'll need our merge agent handler, product as well and maybe merge gateway. For like large AI companies, it's usually like the connectivity that we're really, really a part of. Yeah. And then for SaaS platforms, to be honest, like it could be all three.
00:10:52 · Shensi Ding, Gil Feig
[00:10:52] S2: The types of products that they're probably purchasing defer a little bit. And so we're able to, we're able to have a, like, a guess on, like, what what products they'll be mostly interested in. So for, large financial services, usually, it's probably, like, our unified API for deterministic use cases. Or if they're building some kind of, like, agentic product, then they'll need our merge agent handler, product as well and maybe merge gateway. For like large AI companies, it's usually like the connectivity that we're really, really a part of. Yeah. And then for SaaS platforms, to be honest, like it could be all three. [00:11:24] S0: I think one other interesting difference that we've started to see is when people are buying us for AI use cases, they actually don't really know what they're looking for as much as it was in the past. Right? Like, yeah. Would You know, two, three years ago, we go to sell our unified platform to, you know, a classic SaaS company. They have seven people who are API experts on the call asking detailed questions around rate limits and how it handles this and that. And now we go on the call and they're like, sorry, we need a chart of how this works because we don't know the MCP protocol. Like, we just need to understand, here's our software. Just like, tell us, is this is this gonna work with it or not? We're, a big part of that is like, it's forcing us to evolve now, adapt our product to what people think that they want when no one really even knows what they want right now.
00:11:24 · Gil Feig, Molly O'Shea
[00:11:24] S0: I think one other interesting difference that we've started to see is when people are buying us for AI use cases, they actually don't really know what they're looking for as much as it was in the past. Right? Like, yeah. Would You know, two, three years ago, we go to sell our unified platform to, you know, a classic SaaS company. They have seven people who are API experts on the call asking detailed questions around rate limits and how it handles this and that. And now we go on the call and they're like, sorry, we need a chart of how this works because we don't know the MCP protocol. Like, we just need to understand, here's our software. Just like, tell us, is this is this gonna work with it or not? We're, a big part of that is like, it's forcing us to evolve now, adapt our product to what people think that they want when no one really even knows what they want right now. [00:12:04] S1: That's so interesting. So what is, I mean, I guess to distill that down further, what is the sales experience in the AI world? Like, people just don't they
00:12:04 · Molly O'Shea, Shensi Ding, Gil Feig
[00:12:04] S1: That's so interesting. So what is, I mean, I guess to distill that down further, what is the sales experience in the AI world? Like, people just don't they [00:12:13] S2: don't really know Prescribe or have to say, oh, we've seen this from other customers. Like, these are what best practices are. A lot of times they don't have experience with, like, partnerships for these different integrations. They're not sure like what the best end user experience is. So we'll just We have to use our experience to kind of guide them through the best way to build. But also a lot of these AI companies, they purchase much faster, like large financial services, like the deal cycles are definitely just longer. And for SaaS platforms, shorter, because sometimes we're selling to an existing product that already has product market fit. If it's a newer product, they're also like a little bit unsure of what adoption might look like. And for these large AI companies, it's, it's really fast, because the competition is just so fierce. [00:12:51] S0: Even a lot of times they come into calls and we're like, okay, this is what a POC would look like. They're like, oh no, we already had our agent build into it. We know it works. We just want to make sure, you know? [00:12:59] S1: Yeah. Really? Yeah. They do the proactive approach there? [00:13:02] S2: A lot of times. Yeah. [00:13:04] S1: And so what are their biggest use cases for that? What are they dying to have ASAP?
00:13:04 · Molly O'Shea, Shensi Ding
[00:13:04] S1: And so what are their biggest use cases for that? What are they dying to have ASAP? [00:13:08] S2: A lot of times it's like specific deployment options. Mhmm. So they'll have like specific security requirements. They might want something custom. They might want specific connectors that we don't currently offer. But they've already done the diligence where we are the best partner. But yeah, usually the deployment options are like the big, the big part that we end up having to work with them on.