The control plane for AI agents operating production databases.
Agents resolve incidents and automate operations on your live data. Every action is policy-checked, approved, and audited.
PostgreSQL
MySQL
MongoDBOracleMicrosoft SQL ServerIBM Db2Amazon DynamoDBAzure Cosmos DB
Redis
Apache Cassandra
MariaDB
Snowflake
CockroachDBAmazon Aurora
Google Cloud SQL
ClickHouse
ElasticsearchNeon
Supabase
TimescaleThe problem
AI on your data is easy
to want. Hard to trust.
Everyone wants it
Teams want agents that act on live data, not dashboards that only read it.
One mistake is catastrophic
A single action can drop a table, leak data, or blow the cloud bill.
So agents stay in a demo
Sandboxed and walled off from the real production database.
The fix
Datapace changes that.
Governed and context-aware access to production. Every action is policy-checked, approved, and audited.
See how it worksEvery action
How an action flows
Every action, through one control plane.
Control PlaneWhat we do
Two jobs on your production data. Run it, then get value from it.
Agents operate your databases day to day, then put the same governed data to work with ML. One safe foundation, two kinds of value.
Pillar 01 · Operations & governance
Agents that run your databases.
Day-to-day operations and the governance underneath them, executed by agents and fenced in by the control plane.
- ✓Resolve incidents. Detect, diagnose, and fix issues automatically.
- ✓CI/CD database checks. Catch schema migrations and N+1 queries before they ship.
- ✓Migrate databases. Plan, validate, and execute migrations between engines and clouds, with safe rollback at every step.research-backed
- ✓Data quality & lineage. Semantic quality checks and full lineage, so agents act on context they can trust.
- ✓Optimize cloud spend. Right-size queries and resources.
Pillar 02 · Data valorisation
Turn that data into value.
Agents run adaptive models on your live operational data, surface what matters, and react in real time. Same governed foundation, no new pipeline.
- ✓Predict & forecast. Demand, cost, and capacity from live data.
- ✓Adapt & react. Models retrain as operations change, agents act on the signal.
- ✓Same governance, same audit trail.
Once production data is safe to use, agents can run live models on it, not just read it.
Use cases
What teams run on Datapace.
The same safe foundation powers both pillars, keeping production healthy and turning its data into value.
Autonomous DB operations
Agents watch your databases 24/7, catch anomalies before they become incidents, and fix routine issues on their own, escalating to a human only when policy says so.
Safe schema migrations
Plan, validate, and execute migrations across engines and clouds. Every step is policy-checked, reversible, and rehearsed on a clone before it ever touches production.
Fleet & fuel optimization
Route and fuel data is already governed, so agents run adaptive models on it to cut the bill and optimize routing. A new kind of value from the same data.
Why Datapace
Built so agents can act on production, safely.
Not an AI company bolting on data access. We put governance first, so production is safe enough for agents to act on.
Safety-first
Agents never act outside policy, approval, and audit. Trust is the product, not a feature.
Always on
Agents watch and operate your databases around the clock, escalating to a human only when policy says so.
Infrastructure-neutral
Cloud or on-prem, Azure, AWS, or your own hardware. Technology-agnostic, deployed where your data lives, with no lock-in.
Canada, U.S. & Europe
Serving clients across North America and Europe, with data sovereignty built in. Your data stays in its jurisdiction, under its own rules.
We don't bolt AI onto your data. We make your data safe enough for AI to act on. A control plane where every agent action on production is policy-checked, approved, and audited.
Ready to let agents touch production, safely?
Bring a use case. We'll show you what agents can do on your live data, fenced in by policy, approval, and audit.