Documentation & Help

Supported database pairs, known limitations, and migration guides

Create a project, connect a source and target database, and verify both connections before you migrate anything.

Analyze the source schema, review the conversion, transfer the data, and validate that the two sides actually match.

What HIGH, MEDIUM and LOW actually mean in the data-loss report, and which warnings you can accept.

Run read-only SQL against either side of a project to spot-check data after a migration.

Move production traffic to the migrated database, with a verification gate that refuses to flip unless the two sides provably match.

Compare two databases on a schedule and get alerted the moment they stop matching.

Define masking rules once and apply them across projects, with deterministic values that keep joins working.

Give people access to production data without giving them production credentials, with PII masked unless explicitly granted.

Ask questions of your data in plain language, using your own AI provider key, with every lookup shown and audited.

Give an AI agent a scoped, audited door into a database — structured tools instead of raw SQL, with writes gated behind approval.

Commit, branch, diff and merge the contents of a table — including every write an AI agent makes.

Need more help? Use the migration guides or the error reference, or contact your workspace administrator for support.