AI Cockpit
Runtime observability: who is calling what, whether it is compliant, and what it costs.
This page is under review.
- AI-authored curated content. Every claim is anchored to a derived fact, but the wording, emphasis, and pedagogy are unreviewed product judgment.
AI Cockpit is the runtime view. AI Catalog tells you what exists and AI Control tells you what is allowed; the Cockpit tells you what actually happened.
- It answers three separate questions that tend to get conflated:
- Activity — which actors, servers, tools, and resources are being used, and how the pattern is changing.
- Governance posture — which policies are firing, which never fire, and where coverage is thin. A policy that has never triggered is either unnecessary or misconfigured, and both are worth knowing.
- Consumption — token usage and estimated cost, broken down by actor, model, application, and server.
Recommendations are derived from observed behaviour rather than configured by hand: redundant calls, retry loops, and unusually dense sessions are patterns the Cockpit surfaces because they show up in the invocation record.
Provenance
This page is derived from the following implementation sources.
docs/corpus/narrative/concept-ai-cockpit.md
Last verified at commit b61836e.