Ramp's data shows top enterprise AI spenders doubled revenue.
Dave Font#928
the best product we built at ramp was the culture - this is the best articulation i've seen yet from krish @krrishd
Today, Ramp raised $750M at a $44B valuation.
Last time we grew this fast, we were 1/20th the size.
For 2000 years, business was built on two pillars. Today, a third: intelligence.
It’s your least governed cost. It’s also your single greatest opportunity.
Positive users praise Ramp's $750M raise at $44B valuation along with its culture and multi-model AI spend routing, while negative users call the culture narrow and doubt the economics of its token models.
As I wrote this, I saw X go into meltdown over tokens.
You've seen the headlines: “Uber blows yearly AI budget in just one quarter.” “Meta employee burns 281 billion tokens in April.”
But, the problem isn't spending. Spending works. Since 2023, the top quartile of our AI spenders doubled their revenue. The bottom quartile? Flat.
It's blind spending. We don’t know which spend worked.
A sales team has qualified leads. A support team has resolved conversations. These are units you can measure against. All a token tells you is the meter ran, not whether the work was worth it or not.
Finance says, “half the budget,” engineering says, “double it” and you don’t know who’s right because there is no shared language of value. There’s no attribution, and no attribution means no allocation.
For example, right now, all work, no matter the size or shape, defaults to frontier models. But meeting summaries and calendar updates don’t require GPT-5.5 Pro.
In isolation this seems trivial, but re-route just 10% of a $10M AI bill from frontier to GPT-4 level intelligence you’ve saved nearly one million dollars. This sounds like a made-up stat — it’s not. It truly is that much cheaper.
This is the future of finance: not blindly rubber-stamping or rejecting AI spend, but allocating it with the same rigor companies apply to headcount.
Today, Ramp raised $750M at a $44B valuation.
Last time we grew this fast, we were 1/20th the size.
For 2000 years, business was built on two pillars. Today, a third: intelligence.
It’s your least governed cost. It’s also your single greatest opportunity.
@eglyman @JaredSleeper 🎯 the world will move to ROI per workflow
wrote more about this here last week:
https://www.whatshotit.vc/p/whats-in-enterprise-itvc-500
https://text-incubation.com/ramp
@eglyman yes! multi-model (especially open-source and smaller/faster/cheaper specialized models) for the win!
@eglyman This tacitly implies that the software business model doesn’t really work for AI (since its outputs are non-deterministic)
@eglyman Yep - and that allocation discipline is likely to increase the market size https://www.exponentialview.co/p/does-pricing-shrink-or-expand-markets?r=f84r&utm_campaign=post&utm_medium=web
@vral thank you for having brought me into the fold! seriously a 1-of-1 culture
@eglyman "Tokens are just dollars, agents are just hires." No. A hire can reason. A hire exercises judgment. A hire can refuse. An agent is a stochastic process with a meter attached. The conflation is either naive or convenient.
@eglyman “This is the future of finance: not blindly rubber-stamping or rejecting AI spend, but allocating it with the same rigor companies apply to headcount.”
@vral @krrishd so so so well written
@eglyman The attribution gap is real, and there's a layer under it. Reasoning tokens bill at output rates; agentic runs burn ~1,000x a simple call, and neither maps cleanly to attribution tooling. That's why the bill keeps climbing as per-token costs fall. Thread:
@vral @krrishd The sacred texts
@eglyman > re-route just 10% of a $10M AI bill from frontier to GPT-4 level intelligence you’ve saved nearly one million dollars. This sounds like a made-up stat — it’s not.
This doesn’t just sound like ai slop — it is.
Another huge milestone for @Lux_Capital portfolio co @tryramp - explosive growth and one of the most interesting app companies shipping LLM features & infrastructure today 👇
Today, Ramp raised $750M at a $44B valuation.
Last time we grew this fast, we were 1/20th the size.
For 2000 years, business was built on two pillars. Today, a third: intelligence.
It’s your least governed cost. It’s also your single greatest opportunity.
@vral @krrishd @krrishd really does have motion ngl
@eglyman People don't realize that today's 4B models can run locally on a cell phone and have better than GPT-4o
@eglyman Yes there is a lot we can do, especially multi-provider and OSS. Let's talk @eglyman! Been working on intelligent model routing (gateway agnostic) for 2 years: http://notdiamond.ai
@eglyman 这因果反了吧——不是砸钱AI让收入翻倍，是本来就在涨的公司才烧得起这个钱；优步一个季度烧完年度预算，是因为它打车订单本来就在涨，换个增长停滞的公司同样砸2810亿token，砸出来的只有一张更难看的财报。
@vral @krrishd Accurate
@eglyman Huge congrats!
Today, Ramp raised $750M at a $44B valuation.
Last time we grew this fast, we were 1/20th the size.
For 2000 years, business was built on two pillars. Today, a third: intelligence.
It’s your least governed cost. It’s also your single greatest opportunity.
