Graph Technology Meets GenAI: A Neo4j Perspective

Intel on AI

Connected data is becoming a core competitive advantage in AI, and Neo4j is helping organizations harness it to deliver intelligent experiences at scale. In this episode, Neha Bajwa, Vice President of Product Marketing at Neo4j, explains how graph technology transforms the way companies manage data, derive insights, and operationalize AI by contextualizing information through relationships. Unlike traditional databases, graph databases reveal hidden patterns in highly connected data, making them ideal for modern AI systems that demand rapid, relevant, and explainable access to organizational knowledge. You’ll hear how cities like London use graph-powered digital twins to reduce traffic congestion, and how companies are cutting cybersecurity response times with graph-based detection. Neha also breaks down the rise of GraphRAG—combining Retrieval-Augmented Generation with graph databases to ground generative AI models in structured, connected knowledge for higher accuracy and fewer hallucinations. This approach enables organizations to unify data across disconnected systems without heavy migrations, creating explainable AI critical for regulated industries. She shares how Klarna consolidated 1,200 applications into a single platform using Neo4j’s knowledge graph and agentic AI, building a scalable foundation for continuous innovation. As industries push for AI with real returns, the focus has shifted from asking what AI can do to how quickly it can drive business outcomes with a data infrastructure that supports it. Tune in for a practical, clear look at how Neo4j is helping organizations build connected, AI-ready data strategies to accelerate adoption and deliver real impact.