Revefi governs the cost, quality, and reliability of every token, from the data that drives it to the AI models that consume it and the agents that spend it.
Revefi today announced general availability of FinOps, Observability and Token Economics for AI to govern cost, quality, and reliability across Data, AI, and Agents. The announcement coincides with FinOps X 2026, in San Diego, June 8 to 10, where Revefi will be exhibiting.
On the AI layer, a single user in a Fortune 500 enterprise incurred a $76,000 unexpected token spend for a single AI use case. Revefi caught the above spend for this customer within minutes, and they immediately stopped the unplanned dollar burn.
“Today as enterprises are pushing everyone to use AI across the board, we see AI Agents burning billions of tokens within minutes, with real risk of running out of annual AI budget within weeks or even days. Your AI just lit both your AI and your data budget on fire,” said Sanjay Agrawal, CEO and co-founder of Revefi. “The model was the easy part, knowing what it cost, whether it worked, and if it was even worth it, is the hard part. That’s Token Economics: every token, seen, attributed, and under your control. Because you can’t adopt AI safely at scale if you can’t measure continuously & can’t attribute ROI.”
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Revefi’s Token Economics gives enterprises a single, unified layer to see, attribute, and control the true cost of AI. As organizations push LLMs and AI agents into production, the spend sprawl across providers, models, agents, and users is increasing at an unprecedented rate with no way to trace what happened, where it went wrong, or what it cost. Revefi closes that gap: full user-to-agent-to-model attribution, real-time observability, prompt optimization, and automated ROI on every AI action, across OpenAI, Anthropic, Google Gemini, and Vertex AI. The result is safe AI adoption built on the three things that matter most – spend, trust, and control with value in as little as five minutes and zero-touch.
Revefi reports Token Economics through four lenses that tie spend to value and ROI instead of raw consumption: By Outcome, By Department, Wasted and Optimized. Revefi attributes spend across the full path a request travels. It starts with the user who issues the request, through per-user cost attribution, outlier detection, prompt analysis and tracing, automatically alerts if it goes in the wrong direction, and triggers workflows for model selection, prompt analysis to balance performance and spend.
Proven at the data layer, now governing the full chain
Revefi customers have already cut cloud data and Snowflake warehouse costs between 30-70%. Today the platform is running tens of millions of automated monitors for data freshness, quality, spend increases, schema changes, and query performance for enterprise customers. This is the data-layer foundation that trusted Token Economics depends on.
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