02 / Generative AI · RAG
AI assistant for your own documents
An AI assistant that answers questions from your own documents and data, and shows you exactly where each answer came from. This approach is often called RAG (retrieval-augmented generation), built for accuracy you can check, not just a demo.
Who this is for
Organizations with a real internal knowledge problem, policy documents, technical manuals, support history, contracts, where staff currently search manually or ask around, and a wrong answer is costly.
What usually goes wrong
A basic setup can produce a demo, but not a reliable assistant. The hard part is making sure it finds the right passage: breaking documents up sensibly, ranking the best match first, and citing the exact source so a person can check it.
What you get
- A search system tuned to how your documents are actually structured, not a generic one-size-fits-all approach
- An assistant (chat or API) that shows the exact source for every answer
- A test set of real questions with known correct answers, used to measure accuracy before and after tuning
- A way to keep the assistant's knowledge current as your documents change
In practice
Document · page · span
the exact location every citation points to, checked separately from whether the answer itself was right, Faberiq.ai
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