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One customer asks a question. The answer comes back holding a piece of a different customer's document.
What you'll have at the end
A demo with two fake tenants where the exact collision that leaked one tenant's figure into the other's answer is staged on purpose and now fails: each tenant gets its own correct answer, checked automatically on every deploy.
You need
You already run a multi-tenant RAG application in production with per-request logging (or the ability to add it) covering the tenant id, the retrieval trace, and whether a response came from cache, plus one reported incident where a tenant's answer contained content belonging to a different tenant.
Not covered
Encrypting the vector store itself, building tenant-scoped retrieval from a system that has none yet, or handling a caller using another tenant's stolen credentials are separate jobs; this covers tracing and closing a leak that reached a tenant despite retrieval already being scoped correctly.
Leans on
A shared vector index can let one tenant's query return another tenant's private documents
if the retrieval trace shows a chunk tagged with the wrong tenant, that's the fix you need: building the enforced, tenant-scoped retrieval path this recipe assumes already exists.
Cache semantically similar prompts instead of paying twice
if you're setting up a semantic cache from scratch and want the tenant boundary built in from day one, that recipe covers the exclusion rules and cutoff tuning; this one assumes a cache already exists and something already leaked through it.
Checked 15 Aug 2026
Part of the AI Engineering cookbook