Ramp CTO launches Inspect, an AI coding agent built for enterprise complexity and multi-model flexibility

Speaker 2: Let me tell you about Railway. Railway is the all in one intelligent cloud provider. Use your favorite agent to deploy web apps, servers, databases, more while Railway automatically takes care of scaling, monitoring, and security. Up next, we have Rahul from Ramp, a CTO coming on to TPN. Welcome. There he is. Rahul, how are doing? I'm doing. Thank you so much for taking the time. What's happening? What's going on with this artificial intelligence thing? Anything anything there?

Speaker 6: What's going on with AI? Yeah.

Speaker 2: I mean, here are lot of... But you think it's the real deal?

Speaker 6: I I think it's totally real. I mean, we... There's there's not that many companies who interact with

Speaker 2: a lot a lot of American businesses and and and provide AI to them. So we see it. We see the hype. We see the other side too. And Okay. It's great to bring value as well. Yeah. I mean, I love I love the data that's coming out of the Ramp Economics Lab. I love the products that you're working on. What are customers asking for? And then I'm also interested in what are you seeing that customers aren't necessarily asking for, but you want to be able to deliver before they even know to ask for it?

Speaker 6: Yeah. I mean, so one of the focuses for us is to help businesses automate their finance Yeah. And manage their money, how to control their spend. And we've we've been going after the long tail. So we launched accounts receivable this year. We've been doing bill pay for a couple years. Yep. We we have a bank account now, so Mhmm. Ramp Treasury. Yep. We do travel. So we're really just going after all the spend. Our customers tell us because they... We we hear from them what what they're frustrated about and where where their pain points are. But today, I'm actually here to talk about inspect. We just launched our our coding tool, I'm super excited to talk about Yeah. So Amazing. I mean, we've seen that

Speaker 2: Ramp helping you save time and money, Ramp being the the the software suite for the office of the CFO. It... It's growing in scope because the CFO's remit is expanding across coding spend, so router makes sense in that context. How does this product fit into the CFO's suite, the CFO's strategy, or is this a new motion where you're asking CFOs,

Speaker 6: can we have an introduction to the CTO because we wanna deploy that here? How do you think about how do you think about the actual Yeah. Absolutely. I mean, I think we... When we built Inspect, it was something we built for ourselves. We just wanted a great tool and of course we're building software. We're a company of engineers and finance people and everything else too. We just wanted something that we loved using and we built a lot of software. We want to build software fast. And we found that something was missing in the tools that we we could get. And so that's kind of where we started. I mean, AI is a CFO problem. It will become more of a CFO problem. Yeah. Every CFO is probably sweating right now. They're they're seeing their their bills go up a lot. Yeah. And so by... Just just by that, I think, we... CFOs are are involved and, I mean, we are we we're also... Our incentives are such that we just wanna deliver value to customers. We're we're not we're not aligned with just spending more, and this is historically how the business has always operated. We we don't want you to spend more. We want you to save money and time, and this is just another way to do that. So, I mean, the AI

Speaker 2: coding tool space is so competitive. There's... The landscape's so broad. You have the the IDs, your cursors, your wind service. You have coding agents, your your clogged codes, your codexes, then you have the always on agents, the Grock bots and the dots and the muses and the instincts. How are you positioning this? Where do you want it to grow? Where do you want it to deliver value? What's the unique selling proposition

Speaker 6: right now? Yeah. Absolutely. I mean, I think it's a ram flavor version of a coding agent. The big focus for us was to make sure it works in a company of our scale, our speed, our complexity. I mean, just in terms of how people collaborate across different functions, we made it extremely collaborative multiplayer first, Yep. Works in Slack. Every session is public by default, so everybody at the company can see what's happening Got what you're talking to. You send over a link, and they can continue talking to the agent. Yeah. And it's kind of a group chat. You're just hanging out with the agents and hanging out with all the all the AIs, and it works cross platform across all models. We also like that it works deeply in our RAM context. So it actually can run a version of RAM inside Oh, which is... It's an enormous engineering challenge because we just wanted to get... Have it work with all the stuff we have. And Yeah. When we did it last year, well, or a year ago, we knew that AI is gonna get better. I mean, it was kind of a clear exponential and just gotta, like, kinda keep drawing the line and keep going. We were, like, okay. So this thing's gonna get really smart. And so we needed to get, like, work with our database Sure. Our servers and all the other stuffs going on and download all our code and be able to run and scale really fast. And our engineers were getting very excited. They were using local coding agents. They were like, hey. I need a bigger laptop. And then they would walk around their... The office with their laptops open, sometimes down the street. Yeah. And so we just wanted to move that experience to the cloud. And so the huge emphasis on, in a secure way, getting all of Ramp working. And and now we've since expanded that to code bases of any complexity working inside Sure. Inspect. And so the collaborative angle is a big piece for us and then the complexity as well. How do you think about the

Speaker 2: the value prop, not from, like, the developer experience perspective, but from the CFO's perspective, is the idea that by being sort of an independent third party as Ramp has been in the the big lab race, you can design an agent that uses the best tool for the job. And sometimes that's a OpenAI model. Sometimes that's an anthropic model. Sometimes it's a Gemini model. It might be an open source model. Might be something that's fine tuned. Is there is there a value where you believe that you can drive the cost per task lower than the leading labs can provide if you're all in on one. And so this allows a company to be multi lab, or do you eventually wanna get into inference as well? Like, how deep does that go?

Speaker 6: Yeah. I mean, I think so. The the way I think about it is a lot of complexity that these businesses have to solve for is to get their contacts and their data and their repos set up in a lot of different coding agents. Oh, yeah. And that forces you to effectively pick. And right now, I'm not sure who's who's winning. And the the leading model provider changes very, very quickly, every few weeks. And so if you had to pick it, I don't know what the answer is. And so we wanted to build something that works across all the tools and you can always switch where half the company works on models of this from a certain lab and the other side of the company is very opinionated and so we have every provider running inference here. So we also run our own inference for InSpec and we're happy to work with customers for that as well. Our focus, as you said, is we're not incentivized to just drive up token costs. For us, it's like creepily integrated to RampRouter where you understand where every single session is going, which department is using how much, how many tokens of which model, which service tier and which reasoning effort. There's a lot of complexity that we're we're we're trying to expose to finance people so they can understand and also have controls in addition to engineers on how these dollars are being spent. There's enormous amount of money flowing through, and finance people have to be involved. Yeah.

Speaker 1: How are... I imagine there's, like, a bunch of other products like this that you guys are using right now as internal tools. What... Talk about the decision making process of when you wanna open them up to other people through AMP customer base versus when they should just stay

Speaker 6: internal tools. Yeah. Great question. I mean, there's a ton of complexity in automation that actually inspect sets up for us. And so a lot of our automations and internal tools actually works on top of Inspect's API. So for us, Inspect is an internal coworker. You tell Inspect, hey, this person said they had a bug or something is slow or something is not working or their support they wrote in or we would like to sell to them, so what should we say to them? All all kinds of this this job you can offload inspect because it's plugged into ramp systems. And so we've also since then set up automations to review code to make sure that code is working correctly when it gets to production. Cyber security is a big one for inspect. And so all of these internal automations have now kind of been sitting on top of this. And so for us, it's the bedrock, which sits on top of a router. So we're building these layers of abstractions, and then we can expose to our customers. Well, congratulations on the launch. I'm gonna hit the going for Big one.

Speaker 2: Thank you so much for coming on the show. Very cool launch. Congratulations. Congrats to the team. With the rollout. We will talk to you soon. Have a great rest of your day. Goodbye. Cheers. Let me tell you about the New York Stock Exchange. Wanna change the world? Raise capital at the New York Stock Exchange. It's right down the street from Ramp.