Roadrunner raises $27M from Founders Fund and Kleiner Perkins to modernize AI-era CPQ and revenue infrastructure

Speaker 7: this is not recorded. Yeah.

Speaker 2: There's a lot of training data too. So think about it. Well Later. You, Nate.

Speaker 1: Thank you so much. Our next guest is the co founder and CEO of run Roadrunner, a new company for AI native revenue infrastructure.

Speaker 2: Joubin I like the sound of that, John.

Speaker 1: Mirzadegan. Welcome to the show. How are doing?

Speaker 13: Hey, guys.

Speaker 1: Thanks so much for joining. How are you doing?

Speaker 2: It's happening. Good. Revenue infrastructure. I love revenue and I love infrastructure.

Speaker 1: Yeah. We we we we talked a couple years ago, but for those who don't know you, please introduce yourself and the company.

Speaker 13: I'm Joubin. You guys pronounce my name right. Book first and last, which I was I was impressed by.

Speaker 11: Okay.

Speaker 13: I am one of the co founders and the CEO of Roadrunner. Thanks for having me.

Speaker 1: Yeah. Nice to meet you. Mean, introduce the product, introduce the problem and sort of explain where you fit into the businesses that you're selling into these days.

Speaker 13: Sure. So the backstory is that we incubated the company at Kleiner Perkins. The reason that we did it was because I run a group of CIOs here that meet twice a year and over the course of several dinners, Mhmm. They basically told me it's the most broken problem inside their company. Mhmm. And I actually didn't believe them because I was like, there's no way this has not been a solved problem. And they were like, no. Seriously. And in some cases, it was the number one negative NPS surveyed software inside of their business. I come from sales. Yeah. So I've been the consumer of this problem. Yeah. And I'm like, okay. I understand the problem. So we did a full market map, looked at every company, ended up not finding anything, and so decided to do it ourselves.

Speaker 1: So you said that the existing solutions were low NPS. Was the market also highly fragmented? That's often like the Keith or Boyd lens that he likes to look at, both low NPS and because if it's low NPS, but there's just one monopolist, it might not be a good business opportunity. But what was that market map? How dense was it?

Speaker 13: Yeah. So I think the mother of all tailwinds for us right now, which is the challenge that every incumbent is going through, is that every ten years there's a new CPQ vendor that comes alive. The reason for that is because about every ten years there's a new technology shift that happens. We went from software to SaaS, that became a subscription based billing, then we went from SaaS to AI. AI is very likely going to be a usage or consumption based billing. Mhmm. Every time that happens and there's a new pricing pressure that comes on onto a business or a pricing model, you need somebody that can actually price. Like, if you're a rep trying to do a deal, need you to able to price that deal. If you if the data models with the incumbents were not built to be able to actually price those deals, you're screwed. So every ten years, we have a new technology shift. Every ten years, that puts a bunch of pressure on pricing models. And every ten years, you need to be able to actually get quotes out the door leveraging those new pricing models. And so I think in our case, we are the beneficiaries of that.

Speaker 1: Who what is the sales process like? Because you mentioned the CIOs, the chief information officers. They feel like they have an incredible amount of leverage over the decision of what platform to use, but then the end user is different. So can you sort of walk through the actual user journey a little bit?

Speaker 13: Yeah. I would say the two primary personas are CIOs who are the ones that are responsible for delivering software to an organization and CROs who are the ones that are responsible for getting deals done inside of an organization and the underlying software that they're using is just fundamentally broken. Yeah. So those are like the two people that really matter. The unique thing about this problem is that there's many hands in the cookie jar, which is why it's like a unique problem for a startup to go solve because you have DealsDesk and RevOps and finance and sales and IT. All of these folks touch this business process.

Speaker 2: Yeah.

Speaker 13: And so it's actually quite difficult both to build because you have to build for all of these personas and sell because you have to get all of these people kind of on board with you. Even if you can get all of that done, then you have to convince them that running one of their most important production systems onto an early stage startup makes sense. And so I think that's like kind of the the hill that we that we I guess that we have the honor of climbing.

Speaker 1: Jordy?

Speaker 2: Yeah. Just you're like, I'm pretty good at sales. Why don't I sell something that requires buy in from every part of the organization? Yeah. No. It's a great it's a great challenge, but it seemingly will be incredibly sticky once

Speaker 1: Yeah.

Speaker 2: You get everyone bought in.

Speaker 1: Where where is AI good at this out of the box? Where foundation models are open source useful versus, like, you gotta go build a harness or you gotta go write some SaaS on top of it or get some of your own data and fine tune it? Like, where are we on the frontier of, like, this problem being solved end to end by AI?

Speaker 13: Yeah. So during the the series a fundraise, the the hottest question was why won't Anthropic eat you? Yeah. Basically. And my general point of view is if they go after this, we're all screwed. Like, we might as well put all of our money and all of our eggs inside of the Anthropic basket because this feels like the most esoteric problem that you could possibly go after. I think the the unique thing about this is, you know, at at least at KP, we invested early in companies like Windsurf and Harvey, and we saw what happened when you can point these models at structured and unstructured text in nature. Mhmm. And anytime you can do that, the models are very, very good at reasoning with them. And CPQ is a very similar problem. You have price books, approvals, volume based discounting, all of these rules sit somewhere and the models are very good at reasoning with them. The challenge for us, I think like where our kind of secret sauce is, is that you need to be able to have this agent architecture, call it at the header, then on the y axis, you have a bunch of policy engines that are enforcing a probabilistic system through a deterministic engine. That sits on top of a data model that has to be flexible enough for the pricing models of today and in the future. So the combination of those three things is really our secret sauce. And then obviously, I think the problems that many of these kind of bleeding edge enterprise AI agent companies are running into is like how do you get an agent to work predictably with the harness around it inside of a large enterprise doing something where if we go down, like, get sued. Like, you can't get quotes out the door. Mhmm. And so you can't not get it right. And so I think, you know, in many ways, we are tackling probably one of the more bleeding edge agent problems in the enterprise. Yeah. And that's really where we live is in the enterprise.

Speaker 1: Awesome. Tell us about the round. How much did you raise? I wanna hit the gong.

Speaker 13: We we raised 27,000,000 in There go. Powerful. We announced the seed from KP at 5.2 mil and then 22,000,000 from with Founders Fund Leggeting and KP doubling down.

Speaker 6: Any familial conflicts conflicts going going on on over there? Just kidding.

Speaker 1: Trey Stevens led the round. Don't worry, he's brothers with a mean. Thank you so much for

Speaker 2: coming Oh, I didn't the I didn't even put that

Speaker 1: to you.

Speaker 4: Yeah, yeah, Amazing.

Speaker 2: Anyway. Family business. Love

Speaker 1: it. Love Have a good one. We'll talk to you soon. Thanks guys. Goodbye.

Speaker 2: Thanks guys. Talk soon.

Speaker 1: Up next we have Roman Chernin from Nebius. He's the co founder and chief business officer. If you've been living under a data center