Identity RAG With Zingg and LangChain

Resolve duplicates and name variations before retrieval, so the LLM answers from one complete entity instead of fragments.

Why Identity Resolution Matters for RAG

Without resolution, "John Doe" and "Jon Do" look like two different people to the retriever, splitting relevant context. Zingg clusters records that represent the same entity before they reach the vector store, so the LLM retrieves complete, entity-aware answers, not fragments.

Where Identity RAG Is Already a Fit

Customer service chatbots

Complete records regardless of how a name was entered

Healthcare systems

Patient records linked across multiple providers

Financial compliance

Duplicate transactions or accounts surfaced for fraud review

E-commerce

Unified customer profiles across every channel

docs.zingg.ai: Identity RAG with Zingg and LangChain

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