RAG systems are only trustworthy when content lifecycles are managed. If a document is updated or deleted, users expect answers to reflect that change quickly. In regulated environments, deletion is not optional: you must be able to prove it.
Why deletion is harder in RAG
Deletion is not one action. A single source document may exist in multiple places:
- Raw source storage.
- Extracted text and chunks.
- Embeddings in a vector index.
- Search caches and answer caches (see caching strategies).
Use tombstones and deterministic identifiers
At ingestion time, assign stable identifiers for each source and chunk. When a source is deleted, write a tombstone event and propagate it through your pipeline (see ingestion pipelines). Tombstones prevent reappearing content when connectors resync.
Make freshness measurable
Track freshness as an objective: how quickly updates and deletions appear in the index and in user-visible answers. Treat it like part of knowledge base governance (see knowledge base governance).
Verify deletion, do not assume it
Verification patterns that work in practice:
- Canary phrases. Seed unique phrases in documents and alert if they appear after deletion.
- Source-level audits. Periodically check that deleted source IDs have zero chunks and zero index hits.
- Permission boundary tests. Ensure deletion does not create cross-tenant leakage via caches (see RAG permissions).
Align deletion with retention policies
Deletion workflows must align to retention and audit needs. Keep structured traces (IDs, timestamps, pipeline stages) even when content must be removed, and define what evidence is required for compliance (see retention and deletion and compliance audits).
The simple rule: if your RAG system cannot delete reliably, it cannot be trusted with important knowledge.