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How Ramp cut tool costs by over 70% and scaled AI across the company
Consolidating work (so AI can actually help)
In mid-2024, Ramp set an straightforward internal mission: be the most productive company in the world. They knew AI would be how they got there, but only if it was integrated throughout how the company ran.
At the time, it was not. Work was spread across too many duplicate and legacy tools and too many tabs. Not only did it slow people down. It made it hard to trust what was true.
A question as simple as “What is the latest policy?” or “Who owns this?” could turn into a scavenger hunt across docs, tickets, and chat threads. And without a reliable system of record, AI could not do much more than summarize fragments.
Ramp’s fix was simple in concept, hard in execution: consolidate and connect the work in one place and make the system legible enough that both humans and AI could operate from the same source of truth.
Fast forward to 2025, and you can see that foundation show up in an unlikely place: a slide from Ramp’s internal all-hands. Sitting alongside highlight-reel milestones—fundraising, a Super Bowl commercial, massive product launches—is the full rollout of a new tool the company now runs on: Notion.
With more work centralized and connected, teams spent less time hunting for context and more time making decisions. Ramp cut productivity-tool costs by roughly 70%, and teams reported moving about 3× faster. In a single year, the company’s valuation more than tripled to $32B as annualized revenue surpassed $1B—at a rate 10× faster than the median publicly traded SaaS company. Headcount, however, scaled more modestly because output per employee kept rising.
With that foundation in place, Ramp could build a stack that makes sense:
Notion as the system of record.
AI Notes and Search to capture and find everything.
Notion Agents to turn answers into action.
It’s important to think about productivity as a combination of speed and efficiency, but also quality and output.
Set a philosophy—multiply impact, do not add busywork
Even after Ramp consolidated its work in Notion, the day-to-day friction did not magically disappear. Meetings still dragged on, key context still lived in tools that were not yet connected, and the new system only worked if people built new habits of delegating tasks.
So leadership made the call: assume the AI game has changed, tear up the old timelines and org charts, and stop treating “reasonable” as fixed. The philosophy was not to replace people, but to multiply their impact.
And Ramp put someone in charge of making that real: Ben Levick, Ramp’s Head of Ops and Internal AI.
“Everybody has a responsibility right now to bring their teams up the curve of AI usage and to get them more comfortable being AI native,” said Levick.
Our AI doesn’t just search keywords. It understands our workspace’s actual structure and relationships.
Getting AI into everyone’s hands
Ramp started treating AI as teammates: always-available helpers that take tasks off people’s plates and expand what each team can deliver. They focused first on simple, high-leverage use cases: meetings, where the most important context is created and the most expensive misalignment begins.
Notion’s AI meeting notes changed how Ramp ran meetings. Conversation context stayed close to the work it impacted, decisions flowed into the right places, and follow-ups were easier to track without someone playing human stenographer or project manager.
Then Ramp widened the funnel from “capturing” to “finding and verifying.” AI search got stronger as connectors improved and scoping got sharper, pulling in what still lived in Slack, GitHub, and Ramp’s own systems into concise, accurate answers.
“Our AI doesn’t just search keywords,” says Cameron Leavenworth, Manager of Corporate IT. “It understands our workspace’s actual structure and relationships.”
The final step was giving everyone a personal Notion Agent to take on time-consuming manual tasks. Like a great assistant that has mastered Notion, it helped people draft first passes, analyze and update databases, route requests, and build workflows.
These were not AI novelties. They became reliable accelerants to everyday work.
Our AI doesn’t just search keywords. It understands your workspace’s actual structure and relationships.
