The foundation

Give AI agents safe access to production databases

Coding assistants and autonomous agents are already reaching for production data. Datapace is the layer that lets them, without handing over the keys. Every action an agent takes is checked against your policy, can require human approval, and is recorded in an audit log, across Postgres, MySQL, MongoDB, and more.

How an action flows

From agent proposal to safe execution.

AI agent
Proposes an action
Control plane
Contextmetricsemanticlineagehistory
Policy
against your rules
Approval
human in the loop
Audit
audit ledger
Blocked actions never reach the database
Production DB
Executed safely
Datapace MCP console showing agents querying the governed context graph
The MCP console: agents query the governed context, and every tool call stays visible. Prototype interface, sample estate data.

Policy on every action

Define what agents may and may not do. Datapace checks every statement against those rules before it runs, and blocks the rest.

Human in the loop

Risky actions pause for explicit human approval. Routine ones proceed on their own, so you are not the bottleneck.

A complete audit log

Every action an agent takes is recorded, so you can always answer what touched production, when, and why.

See this on your own data, safely

Bring a use case. We will show you what Datapace resolves on your live database and how the policy gate governs what AI may do.