RAG Architecture Blueprint

Plan an assistant that answers from your own documents, with citations and permissions.

16 checks30 minutes

A general model does not know your catalog, policies, or docs. RAG fetches the right passages at question time so answers come from your facts.

01Decide the approach

Choose RAG over fine-tuning for knowledge that changes or needs citationsFine-tuning is expensive, slow to update, and weak on facts that change.
Avoid stuffing all documents into one giant promptIt stops scaling past a few documents and gets costly fast.
Start with pgvector on the Postgres you already runA dedicated vector store adds cost and moving parts that only pay off at large scale.
List the sources the assistant must answer from, and who may see eachAccess rules added after ingestion are easy to miss and hard to retrofit.