How AI answers from your company knowledge

Instead of relying on a model's general memory, the system first searches your catalogues, policies and documents, then builds an answer from the most relevant passages.

Source quality beats data volume

A small, current and organised library is better than a huge contradictory archive. Remove old versions, date pricing and separate policies by market or branch.

Keep safety boundaries

The system should admit when it cannot find an answer, retain internal source references and send sensitive cases to a person. Trust comes from clear limits.

Register sources before uploading files

Record each source’s owner, update date, permitted audience and replacement procedure. A public guide differs from a customer contract. Filter access before document content reaches the model, rather than merely asking it to keep secrets. Separate changing prices from durable descriptions and retain headings and units with passages so splitting does not disconnect a price from its product.

Test retrieval before answer wording

If the correct passage is missing, changing tone will not repair the source. Inspect Arabic table extraction and scans, keeping references to original pages.

Does retrieval eliminate hallucination?

No. A document’s presence does not guarantee correct retrieval or interpretation. Test combined conditions and exceptions, with an explicit path when evidence is missing. After a price or policy changes, replay a question that returned the old value. Record the source alongside the answer to locate failures, and give knowledge maintenance an owner rather than leaving documents valid indefinitely.