Schema Introspection
Schema introspection is the automatic process of reading a database's own metadata to discover its tables, columns, data types, keys, and relationships.
In Depth
Every major database can describe itself: Postgres and MySQL expose catalogs like information_schema that list every table, column, type, and constraint. Schema introspection queries this metadata so a tool can learn a database's structure in seconds with no manual setup—no uploading documentation, no hand-drawn diagrams. For AI query tools this is the critical first step: the introspected schema is what gets sent to the model so it generates SQL against your real structure rather than a guess. It also means the tool stays current—re-introspect after a migration and the AI knows about the new columns.
How AI for Database Helps
AI for Database introspects your schema automatically on connection, and only this structural metadata—never your actual rows—is sent to the AI.
Related Terms
Schema
The structural blueprint of a database that defines tables, columns, data types, relationships, and constraints.
Schema-Aware AI
Schema-aware AI is an AI system that knows the structure of your specific database—its tables, columns, types, and relationships—and uses that knowledge to generate correct queries.
Migration
A version-controlled change to a database schema, such as adding tables, columns, or modifying constraints.
Data Dictionary
A data dictionary is a centralized reference that documents every table and column in a database—what it contains, what its values mean, and how it should be used.
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