Graph Databases For Enterprise AI episode artwork

EPISODE · Mar 13, 2026 · 26 MIN

Graph Databases For Enterprise AI

from What's Up with Tech? · host Evan Kirstel

Interested in being a guest? Email us at [email protected] AI teams are learning the hard way that dumping more text into a prompt does not guarantee better answers. We sit down with Philip Rathle Chief Technology Officer from Neo4j to talk about the missing ingredient: relationships. When your data is inherently connected, a graph database can turn scattered facts into usable context, so LLMs and agentic AI systems can respond with more precision and less noise.We walk through why graph technology is showing up as a “quiet power layer” behind enterprise AI, from knowledge graphs and digital twins to metadata, lineage, and even relationships between vector chunks for graph RAG. Philip explains the practical difference between raw data and knowledge, why multi-hop reasoning matters in domains like financial services and supply chain, and how an AI system can delegate deterministic parts of a problem to a graph while the model focuses on language and judgment.We also get specific about engineering tradeoffs: why relational databases struggle with constant schema changes, what index-free adjacency means for performance, and how graph queries can run 100x to 2000x faster with less hardware for deeply connected questions. Then we look ahead at where the category is going, including why “graph as a bolt-on feature” often misses the real benefits, plus a roadmap update on Infinigraph for scaling graphs into the 100+ terabyte range. Finally, we cover how AI is making graph adoption easier by inferring graph models from relational sources and helping teams write Cypher queries quickly.If you’re building enterprise AI, graph RAG, or agentic workflows and you care about accuracy, context, and causality, this conversation will sharpen your architecture instincts. Subscribe, share this with a builder on your team, and leave a review. What’s the hardest connected-data problem you want AI to solve?Everyday AI: Your daily guide to grown with Generative AICan't keep up with AI? We've got you. Everyday AI helps you keep up and get ahead.Listen on: Apple Podcasts   SpotifySupport the showMore at https://linktr.ee/EvanKirstel

Interested in being a guest? Email us at [email protected] Most AI teams are learning the hard way that dumping more text into a prompt does not guarantee better answers. We sit down with Philip Rathle Chief Technology Officer from Neo4j to talk about the missing ingredient: relationships. When your data is inherently connected, a graph database can turn scattered facts into usable context, so LLMs and agentic AI systems can respond with more precision and less noise. We walk throu...

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Graph Databases For Enterprise AI

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This episode was published on March 13, 2026.

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Interested in being a guest? Email us at [email protected] AI teams are learning the hard way that dumping more text into a prompt does not guarantee better answers. We sit down with Philip Rathle Chief Technology Officer from Neo4j to talk...

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