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Enterprise Multi-Tenant RAG with Weaviate + LangChain

A production pattern for RAG systems serving multiple isolated tenants from a single Weaviate collection: the architecture behind enterprise internal knowledge bases.

What this covers

  • Multi tenant collection setup with per-tenant isolation
  • Scoped document ingestion per tenant
  • Tenant aware hybrid search (semantic + BM25)
  • Minimal LangChain integration demonstrating tenant aware retrieval
  • Basic handling of empty tenant queries

When to use this pattern

Use multi tenancy when:

  • Multiple teams/BUs share infrastructure but need data isolation
  • You can't afford separate Weaviate instances per team
  • You need tenant-level access control

Setup

Local (default)

  1. pip install -r requirements.txt
  2. Run the notebook top to bottom

Optional: Production (Weaviate Cloud + OpenAI)

See the "MODE 2" section in the notebook for migration steps.

Author

Parikshit Sharma — Principal ML Engineer, production RAG systems