Sources checked
How does RAG work?
The 2020 paper by Lewis and colleagues combines generation with an external document index. In a hypothetical newsroom, the process could compare a release note with an earlier announcement.
- Find relevant documents.
- Pass the useful passages to the model.
- Generate an answer using that context.
- Check that the claims follow from the cited passages.
Where can a RAG answer go wrong?
An answer depends on the whole chain, from search to interpretation.
| Stage | Possible problem | Check |
|---|---|---|
| Document | An outdated release note | Source date and current version |
| Passage | A missing regional exception | Surrounding context |
| Answer | A claim the citation does not support | Claim against the actual passage |
How can you evaluate a RAG system?
Prepare questions with known answers and supporting sources. Include one where the newest page matters, one where an exception changes the answer, and one the documents cannot answer.
What should you ask a RAG provider?
Ask which material the system retrieves, how it stays current, and how you can inspect the evidence. Treat insufficient evidence as a valid outcome.
Common questions
Does RAG eliminate incorrect answers?
No. Retrieval, missing context, and interpretation can each introduce errors.
Does a citation prove a claim?
No. Check that the cited passage supports the claim as written.
What to remember
Retrieving a document helps supply context. It does not guarantee that the document is current, complete, or interpreted correctly.
Sources & further reading
How this story was made
Written by Kristian Kostov with AI assistance and checked against the linked sources. Company performance claims are attributed to the company. Analysis reflects AiLookout’s interpretation; we have not independently tested the products discussed. Cover photography is illustrative and does not depict the specific announcement or product.
Our editorial standards
