The GraphRAG System That Asks Back: Intelligent Probing with Contextual Answers
summary
Claims a production system called AID (Assisted Intelligent Dialogue) that uses Neo4j graphs to turn vague support queries into targeted follow-ups, generating hypotheses from graph neighbors and asking clarifying questions until one path collapses to a precise retrieval. Implementation ties a strategist/ detective/ interviewer/ expert agent loop to vector stores and LLMs; Cisco reports thousands of daily uses and shows improved answer accuracy while introducing dialogue efficiency as a new metric.
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chapters (9)
- 0:00Introduction to GraphRAG challenges
- 4:47Why classic RAG fails
- 7:58Ambiguity in user queries
- 10:02Brainstorming solution approaches
- 15:59Knowledge graph for disambiguation
- 18:27Four-agent system design
- 20:32Live demo walkthrough
- 25:28Lessons from production deployment
- 27:57Key takeaways and conclusion
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