Let AI agents operate production databases. Safely.
Datapace is the guardrail and audit layer for agents on your live data. Every action is policy-checked, requires approval, and lands in an immutable audit log.
PostgreSQL
MySQL
MongoDBOracleMicrosoft SQL ServerIBM Db2Amazon DynamoDBAzure Cosmos DB
Redis
Apache Cassandra
MariaDB
Snowflake
CockroachDBAmazon Aurora
Google Cloud SQL
ClickHouse
ElasticsearchNeon
Supabase
TimescaleThe problem
Everyone wants AI on their data.
The data is not ready for it.
Everyone wants AI on their data
Every team is asking the same question: how do you present your data to the AI? Wanting it is the easy part.
But AI cannot read your database
Decades of schema, derived values, and meaning that lives in people's heads. The builders are gone, so AI guesses.
And one wrong action is catastrophic
A single unchecked statement can drop a table, leak data, or blow the cloud bill. So agents stay sandboxed in demos.
The fix
Datapace makes it ready.
The context layer gives AI what your data means. The control plane governs what it may do. Every action is policy-checked, approved, and audited.
See how it worksEvery action
The platform
One platform between your agents and your databases.
activation
layer
layer
DatapaceWhat 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.
See all use casesAutonomous 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.
Turn governed data into value
Because your production data is already governed, agents can safely run adaptive models on it, for example to cut costs or optimize operations. A new kind of value from data you already have.
Who it's for
Built for teams who work on other people's databases.
Service firms live inside client databases they did not build. Datapace gives them the context to understand those systems fast, and the guardrails to let AI work on them safely.
Safe operations your clients can trust
Every client is asking how to put AI on their data. Answer as the enabler: agent actions gated by policy, approved by your DBAs, and recorded in an audit trail, across every environment you manage.
“Everyone wants to use AI. But how do you present your data to the AI?”heard in customer discovery
Discover source systems in hours, not weeks
Engagements start with the same slow question: what is actually in the client's databases? Datapace resolves schemas into entities, meaning, and lineage, so you scope faster and prototype KPIs on day one.
“I spend a lot of time up front just trying to understand what's in those databases.”heard in customer discovery
Cut migration mapping from weeks to days
Clients hand over decades of legacy data and expect a clean migration. Datapace maps the source system, traces derived values to their origin, and proposes candidate mappings your domain experts validate.
“Clients hand over 25 years of legacy data and say: figure it out.”heard in customer discovery
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.