Ramp raises $1.85B, accelerating past $2B annualized revenue at 100%+ growth as AI spend management becomes a CFO priority

Speaker 1: Woah. Camouflage. Camouflage it with the wall. I see a floating head. That's all I can see in your hands.

Speaker 7: We're in an urban environment. Yes.

Speaker 2: So we

Speaker 7: got to got to blend in.

Speaker 2: That does look like it's designed to not be recognizable by artificial intelligence, which I'm sure we'll talk about. But first, what's the news? What happened? The Glymanator. Tell us the news.

Speaker 1: We... Do we have the gong? Are we ready?

Speaker 7: Are we ready to hit this thing? Alright. We raised $1,850,000,000 and

Speaker 1: I can't hear anything. My ears are blown out.

Speaker 2: Do we need a replay on that?

Speaker 1: Yeah. Let's pull up the replay if we can.

Speaker 2: Pull up the replay.

Speaker 1: That was a clean hit. Bang. Oh, man. Coming in hot with authority, and you kind of held it at the end Oh, too, which was nice. I feel like 2026,

Speaker 7: like, there's been so many fundraisers. They're getting bigger. Your form is really looking good.

Speaker 2: Yes. You got to bring the energy that you feel for the fun to the gong smash. It's really... Because the gong is just one size but the excitement that I feel for the round grows and ebbs and flows and this is the most exciting round of all of course. First question, is the job finished?

Speaker 7: Job's not finished, guys. The job

Speaker 6: is not finished.

Speaker 7: The job is...

Speaker 6: We've got

Speaker 7: a lot of stuff to do. I mean, look, it's... What can I say? We're growing. We're growing faster. Okay. We're growing north in a 100% per year.

Speaker 2: What is growing? Because the core business so solid, so huge, huge market, just in corporate cards, the software for the CFO suite. But then you have a bunch of other products that I feel like because the team is as talented as they are, you're able to deliver a you're able to jump to a great product experience both because you have the team for it, but also there's new technology that's just unlocking new things. And so what... I imagine though they're both growing fast, but what's actually driving? How much time are you spending between both of these? Do they all play together? What what... How do you how do you think about the business?

Speaker 7: So look, I... There's the existing core of the business, let me start with the financials. Yeah. There's metric I track most closely is actually how useful is ramp getting to customers. We talk about growth in those SaaS. And then last, it's all the new products. The majority of our team's time is actually working on products that we haven't launched yet, you haven't seen Sure. Yet. Yeah. And so let's touch on it. I mean, in terms of aggregate growth, said for the first time over the summer, we passed more than $2,000,000,000 a year in annualized revenue. It's growing north of 100% per year. And it's... We're growing 25... More than 25% faster than we were this time last year.

Speaker 4: Wow. It's So true true

Speaker 7: acceleration at scale and in part with computers that can think now, it helps us operate a lot faster. There's also in the same way, I think people's expectations have gone up. I mean there are still sadly many people listening to this who know about AI and then they do expenses by hand or whatever. It's crazy. So it's lifted the conversion rates up. More people are switching to ramp in droves and the savings rates are going up too, which is maybe the second area we're

Speaker 2: gonna And are do you starting to see top of funnel, like the first step on the customer journey coming from not the corporate card product to Yes. Okay. So you can actually start with router or another product and then and then actually grow your your footprint. That's very interesting because I feel like... Do I have it correct that prior to the I don't know, you call them like AI enabled products but like the more modern products that you've launched, it was very much like you come in through the corporate card and then maybe you add banking or you add another product bill pay and there weren't as many people coming in through Bill Pay as might in the future come through Router, for example?

Speaker 7: So to talk to each, I mean, has been one of the big growth stories over the past two years. You know, we now have, I'll put it to say, the vast majority of customers are using multiple products, could be card expenses one, bill pay, treasury. We have tens of thousands of businesses that are using our banking product that's growing extraordinarily quickly, so that our businesses on day one incorporate, set up a Ramp banking account and move from there. So we have these doorways in. And you're exactly right. Whereas so much of the history of Ramp was in, is like how do we help you spend less? It's turning into this broader chapter of not just get more of every dollar in terms of reducing spend. It's how do you have your dollars that you do choose to spend generate more revenue for you? And so there are startups coming in using router.com. Glass has been just extraordinary developed, but also too just wrangling and staying on top of AI spend, AI spend management.

Speaker 2: Yes. On that topic, is is router a bet that that expenses and investment and capital spending around AI will be the domain of the CFO suite and that's where you play best? Or is it a bet that RAMP can speak to CTOs and technologists who will in the future have more domain over asset allocation and the financial profile of their business. Are we going to see CTOs looking more like CFOs or operating like CFOs putting their CFO hat on? Or are we seeing CFOs think, I want to actually have an idea of what our infrastructure is, what our token strategy is, what models we're using? I imagine both are happening, but is there a thesis that you have around what who's who the buck stops with in the token maxing discussion?

Speaker 7: There's like a huge thing that happened that I think is under discussed in just the world of software, which was like, it used to be if you were just like, I don't know, banging on the keyboard, using Salesforce a lot more, might need a new hobby, but like you didn't get like a much larger bill. Like software didn't have a larger marginal cost. And the minute that it became such that if you used more tokens, your bill went up, it meant that software suddenly had marginal costs. In a way, software became money.

Speaker 2: Yeah.

Speaker 5: And

Speaker 7: I just think classically, if you just think about it structurally, organizations were really allocating dollars in two ways. You could hire people or you could hire, you know, vendors to go take care of stuff for you. In software and AI spend has become this like third way to buy things. It sort of behaves like people in that your agents hire other agents who hire other agents and subcontract others. Most spend is actually agentic in nature if you really look at how these things are growing, and yet, you're kind of renting intelligence. I think that organizations just lack the basics of... Many companies have payroll systems. They have ramp, right, to go look at their vendor systems, but have lacked oversight and governance around managing the sales spend. So part of the thesis is that as as as AI becomes one of the the core inputs to how companies operate, organizations will similarly need tools to go manage it. So so that's just like the the macro way we're thinking about it. On your question of like, where is it... Who's responsible for it? I think what I see happen time and time again is like engineers go off to go build something and either they hire a... You know, if it's startups, a very forward thinking, agentic, you know, AI built CFO and it's all fine. Or what's happening in enterprises all day is things are fine that the bill trips past X many millions of dollars and the CFO's like, What in the heck happened? And they crash into the office and go. And I think that's happening more and more. What I would say is like I just think there will be a convergence. You could not think too much about capital allocation in a previous world where software didn't have marginal cost and now you have to.

Speaker 2: So capital allocation, the new core skill? Taste is out. We need to get everyone thinking about capital No. Mean this seriously because I'm sure there's a lot of ramp customers where they're like, yes, we spend on AI and that means a $200 a month plan and look employees, don't blow through your plan because there's no more where it's coming from. And you have a role to play in there. But I'm wondering if you're seeing a shift where even small businesses, even businesses that would normally just be like, hey, yeah, use the free plan, $220 a month here. We'll get you on the corporate plan a little bit are going to be thinking about AI inevitably as a marginal cost that is API pricing and they're going to want a router product.

Speaker 7: Absolutely. And look, like I think one of the... I think both sides of the debates are, like, very silly in some ways. Like, you you have... Like like like CFOs saying, like, hey. I'm trying to go minimize my token cost. What's my cost per token? We need to go and drive costs down. And labs are saying, My token is not equivalent to your token. The tokens are not the same. And the reality is like, if some business owner said to you, Hey, spend a million dollars a year on salespeople, and another one said, I spend $10,000,000 a year on salespeople. And you ask which is better, you'd say, I have no goddamn idea because what are you getting for that dollar? You need to connect it. Need to kind of ask, like, for this input, what is the output? And I think the way in which these systems are very incomplete and RAMP is ultimately seeking to complete that loop of for every dollar that's going out, what is the return on intelligence? Does it go into your books and record? How is it accounting for? What revenue can you see that directly that's connected? And what I would say is when you look at companies that are spending on AI, they are not always as precise, but you can see in raw terms, in very blunt terms, that companies that do spend are clearly seeing a return.

Speaker 2: Yeah.

Speaker 7: They are growing faster. You just think about, you know, we did this study about six months ago where we looked at does spending on this actually generate faster growth? And it's very clear conclusively of organizations that are spending on AI are seeing an acceleration. So there is a return, and I think it will become quite scientific over the course the coming months.

Speaker 1: So does that mean you guys end up building something like an attribution tool? Because like Ramp is a good example of this where like you're encouraging a lot of spending, lot of experimentation, but it's so hard to attribute growth to spend on AI, which is a lot of why that there's people... Otherwise smart people that are saying like this stuff just doesn't work. Like it's good for this one narrow thing. Mhmm. But like very clearly it's like, well, it sped us up a little bit here and it sped us up a little bit here and it pulled forward this launch, you know, by a week instead, you know... So we launched this eight, you know, eight weeks earlier and then there's the sort of like comp... Like, it's basically like compounding in different ways across so many different parts of the company. It's helping you generate revenue in ways. It's helping you save money in different ways. The net result is like you're building a better business. But like the attribution feels like the hardest hardest thing, but something that you

Speaker 7: guys are like uniquely suited to solve. We're very embedded because we see the dollars going out. We connect to the accounting system and you can see what revenue ultimately comes in. I mean just at ramp, like where it ramped it was the first part of the business that used AI in a heavy way. It was go to market.

Speaker 2: Oh, yeah.

Speaker 7: It was sales. Yeah. It was actually we could show that the use of GPT-three when it was a research project actually resulted in more meetings booked for our sales development reps and we could actually look at what is the raw number of dollars spent versus the revenue that that team is able to bring in, and you could see that up. And so when you see products like Glass, which we announced earlier in the week and thousands of companies signed up, we're onboarding folks as fast as we can, All that intelligence where not only is it connected and built into the systems you have, but things you would expect of who's spending it, attribution. Did we pick the right model? Router.com, right, is powering all of it to make sure that you're ultimately saving to the accounting attribution is all done and you see that loop. And so it allows you to actually say like, Am I growing faster? And am I seeing higher and higher returns from my spend on AI? And that's what we're aiming to do. And so when we talk about kind of the end of the beginning and what chapter two is about what you can build as a customer of RAMP, that is what we're running towards. We want to make every dollar an hour, whether it's on people or on AI or both, truly go further. That's what drives us.

Speaker 2: I love it. Well, on the new round. We're going to hop on with Christian Jensen from Dragon Ear to talk more about

Speaker 1: the Amazing milestone. But have a great weekend. Amazing timing yesterday with the Roadster race.

Speaker 2: The Roadster?

Speaker 1: I mean I it was clearly like anywhere. It's clearly like a nod to the... It was clearly a nod to the I new mean, they didn't... They clearly didn't need the ramp to do a kickflip.

Speaker 2: No. Right? They could have used a half pipe. They could have used anything that sound like ramp but... It was

Speaker 1: a little salute down from Texas.

Speaker 2: It was great. But congratulations. We'll talk to you soon.

Speaker 1: Great stuff.

Speaker 6: Great to see

Speaker 1: you, Eric.

Speaker 2: Have a good one. Congrats. Let me tell you about Codex. Codex is a powerful workspace for getting work done with AI agents whether you're writing code, analyzing data, creating content or automating business workflows. Codex helps you move projects forward from start to finish.