Monitor and control your AI spend on every provider on Our early users save 40% on average. Every week, the price-intelligence-latency frontier shifts, and we expect this trend to continue. Tradeoffs between latency, reasoning, cost, service tier, open source and closed source models are shifting constantly. Router sends every request to the model that's actually best for the task and helps you control what tokens you buy. We benchmark it against real work: ~40% lower cost for the same outputs. Today we're opening it to everyone. Two lines of code or just change your base URL. No @tryramp account needed. Free through 2026, first $26 on us. Get an API key today at

Augustus has raised 180M$ on 1B$ to build the Global Dollar Bank. The dollar is the best product in the history of the world - with infinite global demand. But International Fintechs and non-US banks are left with two unsatisfying options to access it: Either they build on legacy clearing banks that are slow and unreliable, or they interface with middleware providers that don’t move and hold dollars directly, but themselves rely on underlying legacy banks. @augustus_bank collapses this stack by combining two things: direct dollar access and Marble, our proprietary bank core, built around intelligence and made of code. If you’re looking to build on the dollar - message me directly or check us out at

AI is extremely good at spending your money very quietly. our own token spend went from a rounding error to more than 10% of payroll in a year. one week in May we burned through $1.5 m. our CFO didn't love telling me that number, and he really didn't love telling the internet. but every finance leader we talk to is living the same story. the bill keeps going up and teams can't answer basic questions about it. which team is driving it? which models they're using? what changed this month? whether a cheaper model would do the same job? so finance gets two bad options: keep paying and hope, or cut broadly and slow down the work that's actually compounding. we built a third one. Ramp now connects to OpenAI, Anthropic, Gemini, Cursor and pulls it all into one place. see it, understand it, control it - down to a single API key. built with 1,000+ companies managing 100T+ tokens a month, and now spending less than they expected too! try it today at

Introducing PorTAL: Portable Task Adapters for LLMs. A novel recipe to cheaply port fine-tuning between models. It matches per task LoRA accuracy at half the cost, lowering the switching overhead of adapting tasks across LLMs. At Ramp, every new model release used to mean retraining our fine-tunes from scratch. PorTAL learns the task once, then efficiently refits it onto any new base model, even across model families.

Today @karimatiyeh and I are both taking new titles as Co-CEOs of @tryramp. If you know us, this won't feel like a change. From when we first started building together twelve years ago, our partnership has run on a couple of motivating principles. On decision-making, we trust each other completely to make critical calls for the company across every function. And on organization design, technology is not a distinct part of the company - it is the entirety of it. That is why Karim has for years directly managed risk, operations, and marketing. Most importantly, at Ramp there is no line between the people who build and the people who do everything else. Everyone is a builder. For the last 2,656 days, we have run the company this way. This only makes it formal. We thought it was important to do it now because of how we see the AI exponential reshaping what Ramp can be. Decisions of company strategy are increasingly decisions of technology and systems design. We have always believed every function should be approached as a systems-engineering problem (even when the system was primarily human) but the rise of machine intelligence makes this existential. Every part of the company must be positioned to leverage the continued explosion in model intelligence and capabilities. If we do this well, each step-change in what models can do compounds automatically into better products and faster execution without anyone having to rebuild the company to capture it. If we fail to operate this way we will ultimately be outcompeted by a new company that does. We are also making Rahul Sengottuvelu our CTO. @rahulgs has led Applied AI at Ramp since joining us three years ago through the acquisition of his prior company, Cohere. Before that, his first company was building customer-service agents on GPT-3 at a time when almost no one knew what a large language model was, and he has spent every year since pushing the frontier of what existing models can do. He has also been right on nearly every major technical direction in AI well before it was obvious. Building Ramp now means applying AI to every part of it, and Rahul is the person stepping up to lead that work. We are still very early in the history of Ramp. Our current chapter is perhaps the most dynamic, but we have never been more optimistic on where it is going and the mission has never been more important. The businesses that trust us are navigating the same shift we are, and we intend to be there for all of it: managing their token spend, supercharging their finance teams, and helping them get more out of every dollar and hour. - Eric & Karim