A governed agent runtime is an execution environment for AI agents where each connected agent action is evaluated against customer-defined policies before execution.
AI agents act autonomously — calling tools, accessing APIs, making decisions, and executing multi-step workflows. Without governance, those actions are unsupervised and unreviewed. Organizations deploying agents in production have no structured way to apply policies to agent behavior.
A governed agent runtime evaluates each connected agent action against customer-defined policies before it executes. Each governed action receives an explicit decision — APPROVED, RESTRICTED, or ESCALATED — and produces a reviewable record. Governance is built into the execution path for the actions that are instrumented, not added after the fact.
Without a governed runtime, organizations discover agent policy violations after damage has occurred. With one, the actions inside the configured scope are evaluated in advance, producing governed outcomes and a decision record for that scope.
Observability shows what agents did. A governed runtime enforces what agents are allowed to do, before actions execute.
Logging records events after they happen. A governed runtime evaluates actions before execution, producing explicit decisions and reviewable records.
Rate limiting controls volume. A governed runtime evaluates the content and intent of each connected action against customer-defined policies.