{
  "id": 14488392,
  "title": "RAG Tenant Isolation Inside the Vector Index",
  "url": "https://urgent.news/2026/10/14/rag-tenant-isolation-inside-the-vector-index",
  "topic": "tech",
  "section": "Tech",
  "published": "2026-10-14T16:28:27.000Z",
  "source": {
    "name": "Dev.to",
    "slug": "dev-to",
    "url": "https://dev.to/ahmad_hassan_6433415b38c6/rag-tenant-isolation-inside-the-vector-index-1moi"
  },
  "original_language": "en",
  "account": "To build a multi-user RAG (retrieval-augmented generation) application, search the entire collection and filter out any chunks that do not belong to the current user. Although this approach passes tests on a single user's laptop, it fails when multiple users are involved. For instance, if fifty people have uploaded contracts with termination clauses and you ask for the eight nearest chunks to the query \"how do I terminate early?\", the filter will only keep one or two relevant chunks, leaving the assistant with limited information to provide a satisfactory answer. The problem lies in relying on a filter implemented in application code, which can be easily refactored by tired developers. A better solution is to incorporate the filter directly into the vector search index definition, as demonstrated in the Retrivo Vault system. By doing so, the search engine will only consider vectors belonging to the current user, ensuring that each user's queries return relevant chunks without interference from others. The implementation requires declaring the userId as a filter field alongside the vector field in the index definition and passing the filter to the same stage that performs the nearest neighbour search. This method ensures that the search returns the best eight chunks from the user's own documents, improving the quality of the generated answers as the user base grows.",
  "summary": "Put the user filter inside the vector search itself. If you search everything and remove other people’s chunks afterwards, those chunks still use up the slots you asked for, and one forgotten line of code puts a stranger’s document into someone else’s answer. The version most apps ship first The obvious way to build a multi user RAG app is to search the whole collection, take the best matches,…",
  "key_points": [],
  "editors_take": null,
  "illustration": null,
  "coverage": {
    "outlets": 1,
    "also_reported_by": []
  },
  "ai_generated": true,
  "disclaimer": "Summaries, key points and the editor’s take are written by software from other outlets’ reporting and may contain errors — always check the linked original."
}