Turn your databases into leverage.
One tool to understand, run, and govern your databases across engines, with AI agents that improve your database workflows.
PostgreSQL
MySQL
MongoDB
Oracle
Microsoft SQL Server
IBM Db2
Amazon DynamoDB
Azure Cosmos DB
Redis
Apache Cassandra
MariaDB
Snowflake
CockroachDB
Amazon Aurora
Google Cloud SQL
ClickHouse
Elasticsearch
Neon
Supabase
TimescaleDatabases outlive their engineers.
Routine work becomes archaeology.
- 01
Several engines, decades of schema
Mid-size and large estates run several engines, often inherited or acquired. What the data means lives in a few people’s heads, and people move on.
- 02
So routine work is slow and risky
Right-sizing, upgrades, cleanup, migrations: each starts with weeks of senior-engineer archaeology, and each risks touching something nobody understands anymore.
- 03
And now AI wants in
Every team wants AI on its data. Without governed context, agents either guess or get raw access, and one wrong statement is an incident.
Datapace fixes the base.
One graph documents what is in each database, what it means, and the infrastructure around it, confirmed by your experts. Agents propose the routine work on that evidence and your team approves. Every AI system reaches production data through governed context, never raw access.
See how it worksEvery proposed change is
- backed by evidence
- approved by your team
- recorded in the audit trail
Months of senior‑engineer archaeology, replaced within days.
One tool for database teams to understand, run, and govern their databases across engines, with AI agents that improve their database workflows.
Today. Several engines, decades of schema, meaning in a few heads. Every change starts with weeks of senior-engineer archaeology.
With Datapace. One graph your experts confirmed, with the infrastructure around it. Agents propose right-sizing, upgrades, cleanup, and migrations with the evidence, and your team approves.
What is in each database, what it means, and the infrastructure around it: cost, usage, freshness, performance.
- FinOpsright-sizing, idle databases
- Performanceslow queries, upgrades
- Qualitychecks, drift
- Migrationfield-level mapping
- Documentationliving docs
Each proposal comes with its evidence. Your team approves; nothing runs on its own.
Understand, run, and govern every database you own, from one graph.
Datapace reads your databases, infers what the data means, and has your experts confirm it. The same graph tracks the infrastructure around each database, so routine work surfaces with its evidence.
Context
- Connect with scoped, read-only access. Which databases and environments Datapace may read is agreed with your team before anything connects.
- Infer what the data means. Entities, measures, relationships, and lineage, inferred from schema metadata, workload signals, and sample structures, each with a confidence score.
- Your experts confirm it. A few working sessions turn proposals into a model your team stands behind: living documentation people and AI can trust.
- Track the infrastructure on the same graph. Instance class, storage, cost, performance, usage, and freshness sit next to the meaning, for every engine you run.
Automation
- See the routine work with its evidence. Right-sizing, engine upgrades, idle databases, and slow queries surface in one place, each with the evidence behind it.
- Agents propose, people approve. FinOps, Quality, Performance, and Migration agents draft the change on that context. Your team reviews and approves; nothing runs on its own.
Governance
- Every action inside policy. Policy checks, human approval, and an audit ledger on everything an agent or a person does through Datapace.
- Governed context for every AI system. Copilots, BI, and MCP clients reach the confirmed graph through the same gate, never raw access.
Then give every AI system governed context, not raw access.
Copilots, BI, and agents reach production data through the same confirmed graph over MCP, inside policy, approval, and audit. No second copy of production, no new pipeline.
What teams run on Datapace.
The routine work of running databases, proposed by agents on one confirmed graph and approved by your team.
See all use cases- amount_centsOrder amount, in cents0.94inferredConfirmed
- statusLifecycle state of the purchase0.88inferredConfirmed
- refund_ofRefund of an earlier purchase0.71inferredTo review
Confirmed by your experts in a few sessions, kept current as the schema changes.
Today. What each table means lives in a few heads, and the last data dictionary drifted the month it was written.
With Datapace. Entities, relationships, and meaning inferred from the source and confirmed by your team in a few sessions, kept current as the databases change.
Built for the teams that run the databases.
In-house database teams at mid-size and large companies, the managed-service providers who run databases for many of them, and the integrators who move their data. Each gets one graph to work from and agents that draft the routine work.
Understand the estate you inherited
For in-house database teamsSeveral engines, decades of schema, acquired systems, and the people who built them gone. Datapace gives your DBAs, platform engineers, and data engineers one confirmed graph to work from in days, so they can work on better things.Explore estate documentationfrom archaeology to a confirmed modelOne tool across every client’s engines
For database MSPsYour team runs Postgres, SQL Server, Oracle, and more for dozens of clients. Datapace documents each estate on its own graph and surfaces right-sizing, upgrades, and idle databases per client.“Everyone wants to use AI. But how do you present your data to the AI?”heard in customer discoveryExplore Datapace for MSPsper-client policy, approval, and auditCut migration mapping from weeks to days
For migration and ERP integratorsClients 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 discoveryExplore ERP data migrationdiscovery to validated mappingWant to see it on your own schema?
A 30-minute call with the two founders. Bring one database; you leave with a first graph of what is in it, what it means, and what your experts would confirm.
Catalogs describe.Datapace governs.
Datapace documents what your databases mean and what runs them, has your experts confirm it, and keeps agents and AI systems inside governed context. The rest is decided with each partner, not imposed by the product.
- Validated, not guessed
- Every inferred meaning carries a confidence score and is accepted or rejected by one of your experts. Nothing enters the graph unvalidated, which is what makes it documentation people and AI can trust.
- Your model, our context
- Bring your own LLM. Datapace is the graph and the gateway, never the model.
- Fits your constraints
- Deployment, access, and data handling are designed with each partner, engagement by engagement, not imposed by the product.
- Canada, U.S. and Europe
- Built in Montréal to serve North America and Europe. Data residency and handling are worked out with each partner, in its jurisdiction’s terms.
We don't bolt AI onto your databases. We fix the base, so you can work on better things.
We go to market with partners.
Datapace is built with the consultancies and advisors who already serve the organizations we serve. They bring the industries, the delivery, and the governance practice. We bring the graph, the agents, and the controls that make database work faster and safe for AI.
Technology partner helping manufacturing, supply chain, and retail companies modernize systems and turn operational data into practical solutions. Tallinn, Estonia.
AI advisory helping organizations find where AI creates real business value, put a dollar figure on it, and set the governance rules to deploy it responsibly. Montréal, Canada.
Ready to turn your databases into leverage?
Bring one database. We will show you what Datapace reads on it, what your experts would confirm, and what the agents would propose first.