← back
Graph Intelligence: Enhance Reasoning and Retrieval Using Graph Analytics - Alison & Andreas, Neo4j
Takeaway
Layering graph analytics over vector RAG adds the structural context single-document retrieval misses, especially for relationship-heavy enterprise data.
Summary
- Neo4j DevRel argues vectors-only RAG returns disconnected 'index cards' — knowledge graphs preserve the relationships among those cards.
- Workshop format walks attendees through Jupyter notebooks combining structured + unstructured data into a graph, then applying graph data science (community detection, centrality, etc.) to improve retrieval.
- Addresses temporal data, data volume, and relationship modeling as the audience's top RAG pain points.
- Frames AI engineers as needing both pipes and water — closing the gap between data science and production engineering.
graph-ragneo4jretrieval
Original description
Advanced GraphRAG techniques apply graph ML and algorithms, wrapped into tidy notebooks. About Alison Cossette Alison Cossette is a dynamic Data Science Strategist, Educator, and Podcast Host. As a Developer Advocate at Neo4j specializing in Graph Data Science, she brings a wealth of expertise to the field. With her strong technical background and exceptional communication skills, Alison bridges the gap between complex data science concepts and practical applications. Alison’s passion for responsible AI shines through in her work. She actively promotes ethical and transparent AI practices and believes in the transformative potential of responsible AI for industries and society. Through her engagements with industry professionals, policymakers, and the public, she advocates for the responsible development and deployment of AI technologies. She is currently a Volunteer Member of the US Department of Commerce - National Institute of Standards and Technology's Generative AI Public Working Group Alison’s academic journey includes Masters of Science in Data Science studies, specializing in Artificial Intelligence, at Northwestern University and research with Stanford University Human-Computer Interaction Crowd Research Collective. Alison combines academic knowledge with real-world experience. She leverages this expertise to educate and empower individuals and organizations in the field of data science. Overall, Alison Cossette’s multifaceted background, commitment to responsible AI, and expertise in data science make her a respected figure in the field. Through her role as a Developer Advocate at Neo4j and her podcast, she continues to drive innovation, education, and responsible practices in the exciting realm of data science and AI. About Andreas Kollegger Andreas is a technological humanist. Starting at NASA, Andreas designed systems from scratch to support science missions. Then in Zambia, he built medical informatics systems to apply technology for social good. Now with Neo4j, he is democratizing graph databases to validate and extend our intuitions about how the world works. Everything is connected. Recorded at the AI Engineer World's Fair in San Francisco. Stay up to date on our upcoming events and content by joining our newsletter here: https://www.ai.engineer/newsletter