Your AI agents can now retrieve enterprise records, invoke tools, modify systems, and initiate business processes without a human in the loop. That capability is the point—and it’s also where every existing governance tool runs out of road. LLM gateways, observability platforms, and output guardrails all operate outside of runtime execution. By the time they observe what happened, the action has already occurred.
AgentGuard was built for a different problem. It is an In Flow Governance Control Plane that participates directly in execution—intercepting tool calls before they fire, masking sensitive data before it reaches the model context window, pausing high-risk actions for human approval while preserving execution state, and producing tamper-evident audit records that satisfy SOC 2, EU AI Act, HIPAA, GDPR, and OCC requirements. Download this factsheet to understand the execution control gap that existing tools cannot close, how AgentGuard’s five-component governance engine addresses it across six control points, and what governed autonomy looks like in practice for organizations in financial services, healthcare, insurance, and government.