Chagu: Graph-Powered LLM Shielding and Anomaly Detection for Secure AI Pipelines

Session Track: App Dev

Session Time: 07:30 am - 08:00 am November 6

Session description

This session will introduce Chagu, a novel protocol currently under pre-patent review, designed to defend generative AI systems using graph-based techniques. Talex Maxim will demonstrate how Neo4j empowers Chagu to trace prompt execution paths, visualize AI state drift, and detect anomalies in distributed, multiagent environments. You will learn how to model LLM interactions, suspicious flows, and behavior shifts using graph structures, making use of Cypher queries to identify threats in real-time. This session will provide an actionable blueprint to help you secure agentic systems by combining graph data models, Cypher-powered detection, and open-source anomaly defense strategies. Attendees will walk away with code snippets, graph modeling ideas, and inspiration for combining Neo4j with LLM pipelines, security layers, and data-driven observability.