Keeping retrieval data current in a RAG application
Measure source updates, embeddings, permissions and generated answers as separate parts of the system.
Retrieval-augmented generation gives a model external information to use when answering a question. It does not guarantee that the selected material is current, authorised or correct, or that the model will use it faithfully. The evaluation should follow a source record through retrieval and into the answer.
The retrieval update and evaluation loop
SC-CY-04 · REV A · 2026.07
Update
source / embedding / index
Evaluate
quality and freshness
Retrieve
relevance and access
Answer
evidence and citations
Embedding refresh, deletion and access checks require explicit implementation.
Track the update path
An operational record, extracted text and an embedding are different representations. Updating one does not automatically update the others. Define how changes trigger extraction, embedding and index updates, and how versions are associated. Include deletes and withdrawn documents. A shared database can simplify part of the path, but it does not remove embedding or invalidation work by itself.
Choose and test the retrieval method
SingleStore supports vector indexes, including approximate nearest-neighbour search. Approximation settings, filters and data distribution affect performance and recall. Compare vector, keyword and hybrid retrieval on representative Japanese text, product codes and business queries. A reported benchmark or category ranking cannot establish the accuracy of the proposed application.
Enforce access through the complete path
Apply the intended user and tenant permissions before information becomes context for the model. Check caches, citations, logs and exported results as well as the retrieval query. A source database’s permissions are not automatically inherited by an index or application. Review external embedding and model services, even when the retrieval database is self-managed.
Evaluate the answer as well as the search
Test relevant evidence, answer correctness, source attribution and refusal when sufficient evidence is unavailable. Measure update and deletion delay end to end, including caches. Include changed policies, conflicting documents and attempts to retrieve another user’s data. Retrieval gives an application a way to supply evidence; it does not eliminate hallucinations or make deployment compliant by construction.
// Key Takeaways
What to remember
- Source records, embeddings and caches need an explicit update process.
- Measure retrieval quality with the prospect’s language and queries.
- Test permissions and answer quality across the whole application.
// FAQ
Frequently asked questions
Does storing vectors beside records keep them automatically current?
No. The application needs an update, embedding and invalidation process. Test changes and deletes through the complete path.
Does RAG prevent hallucinations?
No. Evaluate whether retrieval finds suitable evidence and whether the model answers faithfully, cites the right material and declines unsupported questions.
Last updated:
Prepare a Japanese RAG evaluation with traceable data and permissions.
Discuss how your product updates embeddings, applies document access rules and returns sources. StrategyCore can coordinate product demonstrations and technical questions in Japanese and turn the agreed scope into a commercial proposal.