Explore our event offerings for live and on-demand local, global, and digital events.
Check out our on-demand library of content to learn more about graph technology, get a deeper understanding of use cases, and more.
Join us on November 12 for a virtual conference dedicated to Engineering Better Intelligence. We'll explore modern applications, multi-agent workflows, and context-rich systems.
Learn how a knowledge layer gives enterprise AI the context, memory, and reasoning it needs to go from pilot to production.
Join us on September 22 to learn how GraphAware and the Western Australia Police Force are rethinking intelligence analysis with evolving capabilities that uncover relationships and keep citizens safe.
Join us on September 22 to learn how GraphAware and the Western Australia Police Force are rethinking intelligence analysis with evolving capabilities that uncover relationships and keep citizens safe.
AI Engineer Paris 2026 returns to Station F on September 23–24 for two days of technical talks, practical workshops, and AI engineering research.
For another year we’ll be at the UK’s leading data, analytics and AI conference & exhibition to showcase the latest and greatest in graph technology. Speak to our team of experts about how Neo4j and graph can help improve the...
Join us to learn how to transform relational data into a graph model and load it into Neo4j using industry best practices. Design graph data models and import data into Neo4j You’ll leave with the skills to design scalable graph...
Building World-Aware Robots with Agent Memory and Context Graphs
Join us for an exclusive, hands-on experience designed for developers, architects, and application owners looking to deepen their expertise in Neo4j’s powerful graph technology. This in-person workshop will deepen your expertise in integrating GraphRAG into GenAI solutions—ideal for building systems that prioritize...
This foundational course takes you from the basics of Graph Data Science (GDS) to independent algorithm work.
What changed in this room? Spatial memory for physical AI on a Neo4j graph by Jordi Spranger