AI Integrations for Databases
Databases hold your most valuable business data. Connecting AI to PostgreSQL, MySQL, Airtable or Supabase lets people ask questions in plain language, build assistants that answer from your data and automate reports, without giving AI more access than it needs.
What AI can do with a database
Inbound: questions from staff, scheduled report requests and new records from other apps. Process: turn questions into queries, retrieve relevant records or documents, and summarize the results. Outbound: answers with the query shown, charts and scheduled reports. Vector search in databases such as PostgreSQL with pgvector also powers RAG assistants.
Safe access to data
Connect AI through a read-only user or a reporting replica, restrict it to the tables it needs and mask personal or financial fields. Show the generated query with every answer so people can check it, and log usage. Never let AI run write queries on production data without review.
FAQ
Can staff query our database in plain language?
Yes. Text-to-SQL tools turn questions into queries. Accuracy improves with clear table names, documented metrics and example questions.
Do I need a vector database for AI?
For RAG you need vector or hybrid search, but extensions such as pgvector let you add it to PostgreSQL instead of running a separate system.
Is it safe to connect AI to production data?
Use read-only access, a replica where possible, strict table permissions and logging. Keep sensitive fields masked.
