Explore a multi-agent approach to GraphRAG that democratizes knowledge graph construction for research teams. Watch as four specialized AI agents collaborate: analyzing research focus to suggest entities, extracting knowledge from documents in parallel, merging duplicate entities, and optimizing graph structure - all while keeping researchers in control.
The session showcases a production-ready platform where teams upload PDFs, define their research domain, and receive AI-generated suggestions they can refine with domain expertise. Built with Neo4j, LangChain, and deployed on Cloudflare Workers, this agentic architecture dramatically improves extraction quality while maintaining accessibility for non-technical users.
Learn advanced techniques for agent coordination, streaming processing with real-time progress tracking, and hybrid human-AI decision making. The live demonstration processes research documents in real-time, showcasing how agent specialization produces higher-quality knowledge graphs than traditional single-LLM approaches.