Retrieval inside a pipeline
RAG-Integrated Multi-Agent System
A multi-agent chain with retrieval built in as a step — retrieve, interpret, then write.
Best for grounded answers that need interpretationHow it works
The RAG-Integrated Multi-Agent System pattern
This combines RAG with a sequential pipeline. An orchestrator routes the request, a RAG agent retrieves the relevant passages, a reasoning/legal agent interprets them, and a writer agent produces the final explanation for a specific audience.
- 1
Orchestrator
Classifies the request and routes it down the chain.
- 2
RAG Agent
Retrieves matching passages from the knowledge base.
- 3
Reasoning + Legal
Interprets the retrieved text and resolves nuance.
- 4
Writer
Produces a plain-English answer for the intended reader.
Why it matters
Retrieval alone returns raw passages; this pattern adds agents that interpret and rewrite them, so the reader gets a clear answer that is still traceable to sources.
Playground
Run the rag-integrated multi-agent system
Your Question
InputA request about internal policy
Orchestrator
AgentClassifies the request and plans the route
RAG Agent
RetrievalRetrieves matching clauses from the HR knowledge base
Reasoning + Legal Agent
AgentInterprets the retrieved text and resolves nuance
Writer Agent
AgentProduces the plain-English answer
Final Answer
OutputDelivered to the reader