Control what AI agents can do - before they act.
A new approach to governing AI systems at runtime.
Policies evaluated after requests - outside the application.
Policies evaluated at runtime - before actions execute.
Agentic governance is the ability to control what AI agents can do at runtime -
including tool usage, API calls, and workflow execution.
As AI systems become autonomous, they no longer just generate responses -
they take actions. This creates a new need: controlling behavior before execution.
Traditional policy systems operate at the infrastructure level.
Agentic governance moves policy directly into the execution layer,
where decisions actually happen.
Policy moves from infrastructure → execution
Runs outside applications and evaluates after requests.
Runs at runtime and evaluates before actions execute.
Prevents unsafe behavior instead of reacting after failure.
LLMs now execute tools, trigger workflows and interact with systems.
Uncontrolled actions can expose data, trigger operations or cause failures.
Policy must run where actions happen - not after execution.
Control which tools agents can access and under what conditions.
Define what external systems can be called.
Allow or block critical operations before execution.
Control how multi-step processes are executed.
Actra is a runtime policy engine built for agentic systems.
It enforces decisions before execution - inside your application -
ensuring every action is validated in real time.
This enables safe, deterministic control over AI agents, tools and workflows.