Tenant-Filtered Vector Search Needs Matching Embedding Models and Chunk-Level Freshness

The article argues that retrieval systems should embed user queries with the same model used for indexed help-center content and apply tenant constraints within the vector query itself. Filtering after a broad top-k search is described as flawed, since other tenants' chunks enter the candidate pool and displace permitted results. It recommends chunking content into answer-sized units and tracking chunk ID, tenant ID, source revision, and embedding model ID so changed material can be re-indexed selectively. The author also advises keeping telemetry lean, avoiding high-cardinality labels such as raw query text, full vectors, and tenant or chunk IDs. The piece frames these as correctness decisions that apply regardless of which vector database a team chooses.