Context Graphs and AI Memory

​We're excited to invite you to our next Meetup!

​Join fellow graph enthusiasts, Neo4j developers, and members of the AI community as we explore how graphs, knowledge graphs, and context engineering can unlock smarter applications and better answers.

​We look forward to connecting with the community to exchange ideas on graphs, tech, and AI - join the discussion!

​Session 1:
Context Graphs for Explainable, Decision-Aware AI Agents
Andreas Kollegger, Developer Advocate - Neo4j

​AI agents can follow prompts and use tools, but often lack the institutional context needed to explain why a decision is made. That reasoning: policies, precedents, and past outcomes are usually scattered across systems and human memory.
Context graphs capture this missing layer by modeling decision traces over time, including causality and context. By giving agents access to just enough historical and organizational knowledge, context graphs enable more explainable, consistent, and auditable decisions.

​Session 2: tbd