I'm building a multi-tenant app and need per-tenant vector search

A good way to do per-tenant vector search is to combine tenant isolation with a shared vector index or separate indexes/namespaces, depending on your scale and isolation needs.

Common approaches

1) Shared index + tenant_id filter

Store all vectors in one collection/index, with metadata like:

{
  "tenant_id": "tenant_123",
  "doc_id": "doc_456",
  "embedding": [...]
}

Then every search query includes a mandatory filter:

WHERE tenant_id = 'tenant_123'

Pros

• Simple to operate
• Easy to scale initially
• Good for many tenants

Cons

• Must ensure every query enforces the filter
• Slight risk of accidental leakage if app logic is wrong

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2) Separate namespace / collection / index per tenant

Each tenant gets its own logical partition or physical index.

Pros

• Stronger isolation
• Easier to reason about data access
• Useful for large or regulated tenants

Cons

• Operational overhead increases with tenant count
• Too many indexes can become expensive or hard to manage

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3) Hybrid model

• Small tenants share an index with tenant_id
• Large or premium tenants get dedicated indexes

This is often the best practical approach.

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Recommended design

For most multi-tenant apps:

• Use a shared vector store
• Always store tenant_id in metadata
• Enforce tenant scoping at the service layer
• Optionally use separate namespaces for stronger isolation
• Add authorization checks before search
• Test that cross-tenant retrieval is impossible

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Example query flow

1. Authenticate user
2. Resolve their tenant
3. Build search query with tenant constraint
4. Return only results belonging to that tenant

Pseudo-code:

tenant_id = request.user.tenant_id

results = vector_db.search(
    embedding=query_embedding,
    filter={"tenant_id": tenant_id},
    top_k=10
)

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Extra security tips

• Never trust tenant_id from the client directly
• Derive tenant from auth/session/JWT claims
• Add tests for query isolation
• Log and monitor any query without tenant filters
• Consider encryption at rest and per-tenant access controls if compliance matters

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If you want help choosing the right implementation

I can help you design this for a specific stack, like:

• Postgres + pgvector
• Pinecone
• Weaviate
• Qdrant
• Milvus
• Azure AI Search
• Elasticsearch/OpenSearch

If you tell me your stack and tenant scale, I can suggest the best pattern and schema.