What you can do#
Reconstruct agent sessions — See every SQL statement an AI agent executed, with full metadata such as duration, target database, Postgres role, and error severity.
Audit across multiple data sources — Connect to several HM or Loki sources at once and audit clusters across all of them from one place.
Read a flat audit trail — Scan every statement in a session as a single filterable table, optimized for review.
Rely on cached, incremental sync — The application incrementally syncs and caches session data, so audit views load quickly without re-querying the full log history on every visit.
Where to start#
Key concepts — the key terms used throughout the application: sessions, steps, purpose, instances, and how Airman MCP tags activity.
Architecture and data flow — how agent activity travels from Postgres logs into the application.
Deploying and configuring — for administrators deploying and configuring the application.
Connecting data sources — register an HM or Loki instance so its agent sessions appear.
Browsing sessions — find and filter the AI agent sessions detected for a cluster.
Inspecting a session — inspect a single session step by step and read its audit log.
Securing access and handling credentials — authentication, credential storage, and how your data is treated.
Using Agent Governance with Hybrid Manager#
If your Postgres clusters are managed by Hybrid Manager, see Governance in Hybrid Manager for the HM-specific integration details — machine user API keys, HM’s Loki pipeline, and project and cluster discovery.