About
Production agents are only as reliable as they are coherent.
AI agents are moving into customer conversations, operational workflows, and decisions where stale context is not a UX issue. It is a trust issue. The longer these systems run, the more important it becomes that what they know stays current without manual cleanup.
Cerebell is the coherence layer for AI agents in production. It keeps agents current, verified, and usable in real time, so they can continue to operate on the truth as conditions change.
It is not a knowledge graph or a context graph. It is built on a primitive designed for data that changes: verified before it applies, preserved after it changes, current before the next read.
Founder
Ezra Brezina founded Cerebell after more than a decade in enterprise B2B SaaS, helping companies move from idea to production. The conviction behind Cerebell is simple: agents will not be trusted with real work until the information they depend on can stay current without people maintaining it. The company exists to make that a default property of production agents.
What Cerebell Does
Cerebell keeps production agents operating on current records as conditions change. New information is recognized, verified, and resolved before it becomes stale context your agents can reuse.
It runs underneath your existing agent stack: any model provider, cloud or on-prem deployment, prior records preserved for audit, and no manual cleanup loop for the team maintaining the system.