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

Ramp raises $1.85B at $60B valuation as revenue accelerates past $2B

Ramp has closed a $1.85 billion round at a $60 billion valuation, led by Dragoneer with participation from Thrive Capital, Founders Fund, Sands Capital, and Avenir. The company has crossed $2 billion in annualized revenue, growing more than 100% year-over-year and accelerating — Glyman says Ramp is growing more than 25% faster than it was at this point last year. That is real-scale acceleration, not a base-effect story.

“We passed more than $2,000,000,000 a year in annualized revenue. It's growing north of 100% per year. And it's growing more than 25% faster than we were this time last year... In the same way software became software-as-a-service, AI spend has become this third way to buy things — it sort of behaves like people in that your agents hire other agents who hire other agents.”

The AI spend management thesis

The product expansion driving that growth centers on a structural shift Glyman argues is underappreciated: AI gave software marginal cost. When token usage drives the bill up, AI spend starts behaving like headcount — it compounds, it compounds inside agents that hire other agents, and it falls outside the governance tools most companies have built. Most organizations have payroll systems and vendor management. Almost none have formal oversight of AI spend. Ramp is positioning itself to close that gap.

The pitch is that CFOs will inevitably crash into this problem. Glyman describes a recurring pattern in enterprises where engineers spin up AI infrastructure, costs quietly scale past a threshold, and the CFO demands answers. That reactive moment is Ramp's entry point for products like Router and Glass.

Return on intelligence

Glyman's framing for what Ramp is building toward is what he calls "return on intelligence" — connecting every dollar of AI or headcount spend to its output in the books. He argues the industry debate between CFOs optimizing cost-per-token and labs insisting tokens aren't equivalent misses the real question, which is whether a given dollar of AI spend produces a measurable return. Ramp's structural advantage is that it sits across both sides of that ledger: it sees dollars going out and connects to accounting systems where revenue comes in.

Ramp says a study it ran roughly six months ago found that companies spending on AI are clearly growing faster, even if attribution remains imprecise. Glyman points to Ramp's own go-to-market team as an early example, where GPT-3 usage was correlated with more meetings booked by sales development reps and a measurable improvement in the ratio of AI spend to revenue generated.

Product surface

The majority of Ramp's team is working on products not yet launched. On the existing portfolio, Glyman says the vast majority of customers now use multiple products — card, expenses, bill pay, treasury, and banking. The banking product is growing quickly enough that some startups are incorporating and opening a Ramp banking account on day one. Router and Glass represent the newer layer, aimed at managing and attributing AI spend specifically.

Ramp's near-term target is completing the attribution loop — making it possible for a company to ask, for any dollar spent on AI or people, what revenue or efficiency it generated and how it flows through the books. That is the bet behind the $1.85 billion raise.