Graph Database - United Kingdom

This hands-on workshop shows you how to build smarter AI agents: ones that don’t lose context. You’ll use Neo4j’s Model Context Protocol (MCP) to give your agents persistent, graph-based memory, allowing for richer, multi-turn interactions and intelligent behavior grounded in your data.

You’ll walk through the full agent-building process: from setting up a knowledge graph, to integrating GraphRAG for multi-hop reasoning, and deploying an agent with contextual memory that evolves over time. By the end of the session, you’ll have a working, production-ready AI agent you can extend for your own use cases.

Ever wanted to build an agent that can understand your data and answer complex questions for you? In this workshop, you’ll roll up your sleeves and create your own agent in Neo4j Aura, complete with a UI and a real use case around legal documents and KYC (Know Your Customers) checks.

Join us for a live Speaker Panel with select guests from 2025's NODES conference coming in November.
Register to NODES 2025: https://neo4j.com/nodes-2025/

Kateryna Nesvit, Ph.D. - Associate Professor of Data Science, Marymount University | Founder and CEO, AliveMath LLC
Supply Chain Risk Predictions with Neo4j Graph Data Technology
https://neo4j.com/nodes-2025/agenda/supply-chain-risk-predictions-with-neo4j-graph-data-technology/

Christian Franke - SwissDRG
Knowledge Graph of Drugs Data for Swiss Healthcare System
https://neo4j.com/nodes-2025/agenda/knowledge-graph-of-drugs-data-for-swiss-healthcare-system/

Shubham Bakshi - Security Architect, Outshift
Revolutionizing Platform Engineering with AI Agents and GraphRAG
https://neo4j.com/nodes-2025/agenda/revolutionizing-platform-engineering-with-ai-agents-and-graphrag/

Luanne Misquitta - CTO, cMatter
Harmonizing AI and Graphs: Building Intelligent Music Applications with Neo4j and Spring AI
https://neo4j.com/nodes-2025/agenda/harmonizing-ai-and-graphs-building-intelligent-music-applications-with-neo4j-and-spring-ai/

Register to NODES 2025: https://neo4j.com/nodes-2025/

#neo4j #graphdatabase #graphrag #llm #genai #knowledgegraph

We're excited to invite you to our next Meetup, co-hosted with the London Java Community!

Join fellow graph enthusiasts, Neo4j developers, and members of the Java community as we explore how graphs, knowledge graphs, and context engineering can unlock smarter applications and better answers. We’ll also uncover how AI-generated code can be weaponized, exposing hidden vulnerabilities in the software we trust.
Whether you’re curious about building with graph-powered AI or safeguarding your projects from new threats, this meetup will give you insights you can put into practice.

Session 1: The Enemy Within: How AI is Weaponizing Your Code by Steve Poole

There are no black cats, broken mirrors or sudden storms to announce the news. Still, AI-generated code has become a double-edged sword, offering unparalleled productivity while quietly introducing vulnerabilities and weaknesses. Whether through poisoned models, maliciously crafted to inject flaws or poor-quality training data, your trusted AI companion could be a Trojan horse.
This talk unveils the dark side of AI in software development, exposing how attackers exploit AI to compromise open-source projects and infiltrate the software supply chain.
Learn how bad actors leverage sophisticated techniques to embed security flaws in libraries you trust, and discover how untested, AI-generated solutions can open doors to catastrophic exploits.
With real-world examples, We'll dissect how these attacks happen and offer strategies to safeguard your projects.
In the battle for secure software, your tools could be your greatest weakness or your first line of defence. Prepare to confront the chilling truth about AI and your code.

Session 2: WhatsThat? Using graphs and AI to make sense of your friends WhatsApp group by Martin O'Hanlon

Communication, messaging, and memory are complicated. How are you supposed to keep up with it all? It's difficult for you to keep up with the constant stream of messages you get. How can we expect an LLM to do the same? Let's look at how we can use graphs and AI to summarise the complex streams of messages you get in that oddly titled WhatsApp group.

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