Ramp at $32 billion: Money talks. Now it thinks.

In the first year of business, every dollar is a decision.

A $500 software subscription is a discussion. A $5,000 research tool is a debate. Everyone knows who approved what — and whether it was worth it.

Ten years later, the same subscription has empty seats renewing on autopilot, and $5,000 of research slips away as miscellaneous. There’s also a $1.2 million SAP maintenance contract that nobody dares question because “it’s always been there.”

You used to run the business. Now the business runs you. And if you do question an expense, you get a spreadsheet, not an answer.

Every founder is adamant this will not happen to them — but it inevitably does. You start building a product. You end up building a bureaucracy.

Take the average publicly listed SaaS company. Big teams, lots of bloat. They’re growing at 16% per year. What about just the top 10? The best performers. They’re growing at 30% YoY. This is all public data.¹

So when I tell you Ramp's underlying profitability² is growing 153% year over year, that sounds absurd. It’s 10x faster each year than the median publicly traded SaaS company. Our revenue was $500 million 12 months ago, over $1 billion today.

A whole new class of companies have come along. Heavyweights that move like lightweights.

Getting big no longer means getting slow. Let me explain.

The Age of “Thinking Money” (2025 –)

For millennia, money talked — but it didn’t think.

Then AI happened. Suddenly, money was no longer just a number in an Excel sheet. For the first time it understood context, could reason, and act.

Imagine a dollar wants to leave your company. Before “thinking money” it could simply walk out. No memory of what it funded, or knowledge if it was spent wisely.

Now, that same dollar has intelligence. So before it leaves it checks for fraud and if you have permission to spend it. It has memory. So as it moves it leaves a complete audit trail and updates budgets. And it can reason. So once it’s spent it tells you if it was well used, underused, or wasted.

That’s one dollar. The average publicly listed SaaS spends over five hundred million of them each year. What if each one a) was only spent if it should be, b) audited itself instantly, and c) flowed only to the highest-impact projects?

You had a bureaucracy. Now, you have a business again.

If money thinks, what does finance do?

Rather than have me explain, let me show you.

In October, Ramp’s AI made 26,146,619 decisions across more than $10 billion in spend. This is “thinking money” with intelligence, memory, and reason. Here are a few of those decisions:

• Our policy agent prevented 511,157 out-of-policy transactions, saving $290,981,801.
• Our treasury agent moved $5.5 million from idle cash to 4% investments.
• Our fraud agent blocked a $49,000 AI-generated fake invoice.

Our travel agent saved $113.34 for Zain on his trip to New York.

What do all these decisions have in common? They’re objective! Put every accountant in America in a room, give them context and 10 minutes, and they’d all agree. But in practice, thousands of small would-be improvements slip through every day.

Now that all of this is automated, your finance team is free to make a smaller number of higher-leverage decisions. They’re strategists — not clerks. Not catching policy violations, they’re designing policy that enforces itself. Not coding transactions, they’re working out how best to allocate a $500 million budget.

Big decisions. Not the small stuff.

The return of economic productivity

Forty years ago, Robert Solow said “You can see the computer age everywhere but in the productivity statistics.”

And for decades he was right. From 1947 to 1973, U.S. productivity grew 2.8% a year. In the last three decades, just 1.4%. But that was the age of “money talks.”

Now it’s the age of “thinking money.” When thinking money automates the small stuff, companies run better. The median Ramp customer saves 5% while growing revenue 12% year over year.³ They’re closing books in days instead of weeks, running leaner teams, and compounding efficiency gains quarter after quarter.

The promise of the computer age — widely available, cheap intelligence — is only now coming to life, and helping everyday companies get more from their time and money. Finally, we’re proving Solow wrong.

A whole new growth curve

I’d started by telling you "there's a whole new growth curve.” Well, I’d like to end by explaining it.

All the way back in 1967, there was a computer scientist named Melvin Conway. He was frustrated by how slowly software projects were moving at IBM, so he started researching the problem.

Two months later, he published the paper that introduced the now-infamous Conway’s law.

“Your product mirrors the system of the organization that built it.”

In plain terms: the reason IBM’s software was slow and complicated was because IBM was slow and complicated.

So, what if your staff no longer had to book travel, email receipts, update budgets, or chase approvals? What if there weren't three layers of management between spend and strategy?

No, you won’t magically start growing at 100% YoY. But you're building the kind of organization that can.

That’s the second growth curve. That’s “thinking money.”

– Eric