Policy-Aware Agent Control
Building a runtime trust control plane for AI agents that performs identity-aware policy evaluation, invariant verification, audit persistence, and human-readable risk explanations for agent actions using a React frontend and FastAPI/Postgres backend.
Demonstrates how action-level policy enforcement can make AI agent behavior auditable and controllable, attempting to address real risks like data exfiltration and prompt injection in enterprise environments.