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AI agents are powerful, but they are not controllable by default. Most systems treat agent behaviour as something you observe after the fact: logs, traces, dashboards, alerts. That’s fine for debugging. It’s not fine when agents touch real systems, real users, or regulated data. Handlebar exists because monitoring is not control. We’re building infrastructure that lets you put deterministic, verifiable rules in the execution path of AI agents — with hard actions, not suggestions. The same input always produces the same decision. Every decision is explainable. Every outcome is auditable. This matters most in regulated environments (like healthtech, finance, and law), where:
  • You must be able to prove why something happened
  • You must be able to stop unsafe actions before they occur
  • “The model decided” is not an acceptable answer
Handlebar turns AI agents from probabilistic actors into governed systems with enforceable rules.

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What Handlebar Is (and Isn’t)

Handlebar is:
  • A deterministic control layer for AI agents
  • A policy engine that evaluates agent behaviour at runtime
  • A system of record for decisions, not just events
Handlebar is not:
  • Another agent framework
  • A prompt management tool
  • A monitoring-only product
We don’t try to make agents smarter. We make sure they follow rules.