Your best people keep answering questions your documents already answer.
Every repeat question pulls an expert away from their own work.
A confident answer can still be the wrong one.
Make approved knowledge easier to find, check and use.
Keep outdated information out of the answer
Identify useful documents, owners, versions and access rules.
Show where the answer came from
Retrieve relevant material and show the sources behind an answer.
Keep restricted knowledge restricted
Limit retrieval to information each user is authorised to see.
Know when to stop and ask an expert
Forward unsupported or conflicting questions and use feedback to improve coverage.
Questions about answers, access and accuracy
What does RAG mean?
Retrieval-augmented generation combines a search of approved material with an AI-generated answer. It helps connect the answer to business-specific sources.
Can it use our documents?
Yes, subject to source quality, rights, format, access and an agreed update process.
Can it cite its sources?
Yes. Source references should be part of the answer experience and testing.
Does RAG eliminate incorrect answers?
No. Evaluation, source controls, refusals and escalation remain necessary.
Can different teams see different information?
Yes, when the identity and source systems provide reliable permissions that can be enforced.
What if documents conflict?
We agree on source authority and escalation rules so contradictions are not silently treated as certainty.
Can it update CRM or complete actions?
That needs an explicitly scoped workflow or agent capability with separate permissions and testing.
How do we start?
Select a useful set of questions and approved sources for a bounded pilot, then evaluate answer quality with real users.