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Combine Knowledge Graphs and RAG for Accurate, Explainable GenAI has completed, but you can still view the video archive.
Video ArchiveOrganizations are eager to tap into the potential of GenAI — but GenAI apps can’t deliver valuable responses if they’re not based on accurate, relevant data. You also need traceable and explainable responses to understand how your app arrived at its results.
Using vector search alone? Vector search alone doesn’t capture critical connections between data and misses out on valuable context. Then you can’t provide the most accurate, relevant, and explainable responses possible.
You can overcome these limitations with GraphRAG, which combines vector search with RAG and knowledge graphs. With GraphRAG, you can reduce errors, avoid hallucinations, and build reliable, trustworthy GenAI apps fast.
Join us for our half-day virtual event for an overview of how to build smarter GenAI apps with GraphRAG. Don’t miss out on the chance to:
Sign up today to save your spot. You’ll also get on-demand access to the sessions after the event.
Subject to Change
Neha Bajwa, Neo4j
Welcome
Jim Webber, Chief Scientist, Neo4j
Lies, Damn Lies, and AIs – How Knowledge Graphs Keep AI’s Honest
Philip Rathle, Chief Technology Officer, Neo4j
GraphRAG Manifesto
Zach Blumenfeld, Product Specialist, Neo4j
Building Smarter GenAI Applications with GraphRAG
John Stegeman, Product Specialist, Neo4j
Build Your GenAI-Ready Knowledge Graph With Neo4j
Alison Cossette, Data Science Advocate, Neo4j
Neo4j LLM Knowledge Graph Builder: Unstructured Data to Actionable Insights in Minutes
Neha Bajwa, Neo4j
Closing