An artificial intelligence context engine connects a model to multiple organizational sources and selects information relevant to the current task. It can retrieve code, pull requests, design decisions, documents, conversations, ownership records, and previous incidents, then package the most useful evidence into the agent's working context.
A good context engine emphasizes provenance, freshness, permissions, and relevance rather than simply supplying more text. It should show where information came from, respect source access controls, avoid stale or contradictory records, and keep the context small enough for the agent to use reliably.
