Why attend
Learn from the frontlines of AI innovation
Hear how developers, researchers, and industry leaders are using graph technology to push AI forward — from GraphRAG and knowledge graphs to intelligent agents and context engineering.
Build smarter, context-aware AI systems
Discover how graph memory and context engineering are shaping the next generation of AI — making systems more adaptive, explainable, and capable of real-world reasoning.
Connect with the global AI community
Join thousands of data and AI professionals for a one-day online experience packed with technical sessions, demos, and conversations that inspire innovation.
Watch the nodes ai 2026 opening keynote
Exploring Context Graphs: From Data to Decisions
AI models are getting smarter but production systems still fail for a simple reason: they lack context. In this panel moderated by Philip Rathle, WIll Lyon, Animesh Koratana, Lasse Andresen, and Emil Eifrem explore the idea of context graphs as a new foundation for AI systems that can reason, adapt, and improve over time.
What you’ll learn
Knowledge graphs & GraphRAG
Explore how knowledge graphs and GraphRAG connect structured knowledge with generative AI to deliver smarter, context-rich results.
Graph memory & agents
See how graph-based memory enables AI agents to retain context, persist knowledge, and adapt their behavior over time.
Graph + AI in production
Hear real-world stories of scaling graph + AI into production and driving measurable impact across industries.
NODES AI 2026 featured sessions
Building a Customer-Intelligence Brain: How GraphRAG Turns Data into Decisions
This session shows how turning such data into a Neo4j-powered Customer-Intelligence system unlocks new analytical and generative capabilities for business, product, and experience teams.
Agentic GraphRAG: Autonomous Knowledge Graph Construction and Adaptive Retrieval
Traditional GraphRAG systems often rely on manual schema design, handcrafted rules, and fixed retrieval strategies, making them brittle and difficult to generalize across domains.
The AI Agent Memory Landscape
As AI agents evolve from stateless chatbots to persistent, context-aware systems, memory has become the critical differentiator between demos and production-ready applications.
