Operations

Autonomous database operations, inside your guardrails

Datapace is built so agents can watch your databases, catch anomalies before they become incidents, and resolve routine issues inside your guardrails, escalating to a human when policy says so. The goal: fewer pages and less toil, without giving up control.

How operations run

Watched continuously, fixed inside policy.

Production DB
Watched continuously
Ops agent
Contextmetricsemantichistory
Watch
anomalies surface early
Fix
only inside policy
Escalate
when judgment is needed
Every automated action lands in the audit log
Your on-call
Paged only when it matters
Datapace profiling and quality checks on a database table
Profiling and quality checks on a table: the evidence agents and your team share. Prototype interface, sample estate data.

Watch continuously

Monitoring on the same context graph surfaces problems early, before they reach an on-call engineer.

Fix inside policy

Routine fixes run only through actions your policy allows, and only after the relevant gates pass.

Escalate by policy

When an action falls outside policy or needs judgment, it escalates to a human instead of proceeding.

Related reading

Self-driving databases in 2026: progress vs hypeEssay · 13 min readTime-series anomaly detection fails on PostgresPattern · 11 min readThe DBA extinction: what actually disappearedEssay · 11 min read

Related use cases

Safe AI database accessSafe schema migrations

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.

Book a call