FortaifyPrivate RAG
Search your documents without casually exporting the source material.
Retrieval-augmented generation finds relevant passages and supplies them to a model. A private RAG design controls where documents are parsed, embedded, indexed, retrieved, and finally sent for generation.
Plan a private knowledge pilotMap every data hop
A local vector index is only one part of the system. Embedding generation and final inference also receive document content. Choose local or approved customer-controlled services for each step when source material must remain inside the environment.
Permissions still matter
Retrieval should preserve the access boundary of the source. A shared index without document-level authorization can expose material even when the model itself runs locally. Define source ownership, synchronization, deletion, and reindexing before production use.
Test the lifecycle
A useful pilot covers ingestion, indexing, retrieval quality, source updates, deletion, interrupted-worker recovery, backup, and restore. It should also verify that logs and metrics contain operational metadata rather than document text or prompts.