Context Data InterLock

InterLock from Context Data sits between AI agents and your databases, files and APIs, checking each request against roles and policies. It is built for teams putting agents in front of production data who need masking, approvals and an audit trail.

Each agent gets its own identity and key, and access can be limited per source and, for SQL, per table and column. Queries are parsed before they run, personal data such as social security numbers is redacted in results, and risky writes like unbounded deletes wait for a human to approve them in the console, with optional Slack alerts.

It deploys inside your own environment and speaks the Model Context Protocol, the Postgres wire protocol and HTTP, so connecting an agent is a connection-string change. Every allowed or denied request lands in an append-only audit log that exports as CSV, and repeat queries can be served from a per-identity cache.