RAG Business Document Assistant

Businesses drown in unstructured information — invoices, contracts, operations notes, and policy files that no one can search quickly. This project applies retrieval-augmented generation (RAG) to make that knowledge queryable.

How it works

• Indexes the business’s own documents (accounting records, operations files, and more).
• On a question, retrieves the most relevant content and generates a grounded answer from the user’s own files — not a guess.
• Returns answers tied to the source material, reducing the risk of hallucinated or off-policy responses.

Business value

• Cuts manual document-search time dramatically.
• Turns scattered files into an answerable knowledge base with no reorganization required.
• Bridges the infrastructure engineer’s rigor with applied AI — the same pattern used in memory and retrieval systems.