Jul 23, 2026

AI on Your Lakehouse: Context Comes in Shapes, Not Queries — Zach Blumenfeld, Neo4j

AI agents often struggle with context in lakehouses, leading to confident but incorrect answers. This workshop by Zach Blumenfeld introduces three Neo4j graph shapes built on lakehouse data—Connections (semantic layer), Trees (document outlines), and Communities (themes)—to provide essential context, enabling agents to accurately navigate structured and unstructured data, answer complex estate-level questions, and overcome limitations of traditional Text2SQL and vector search.

Jul 02, 2026

Ex-Google Cloud AI Boss: Your Data Is the Real Moat

Andrew Moore, CEO of Lovelace AI, discusses YottaGraph, a rapidly growing, automatically constructed knowledge graph designed as a context engine for enterprise AI agents. He highlights Lovelace's differentiation from public knowledge graphs by focusing on integrating private enterprise data, the engineering challenges of entity resolution and fast multi-hop reasoning, and the critical importance of graph amendability and auditability for mission-critical applications. Moore also touches upon the future of computer science education, advocating for product management skills and emphasizing the strategic importance of domestically developed open-weights models.

Sep 16, 2025

923: Graph Algorithms, GraphRAG and Causal Graphs — with Graph Guru Amy Hodler

Graph analytics expert Amy Hodler explores the power of graph data structures, covering fundamental concepts, graph algorithms like PageRank, and their application in fraud detection and supply chain optimization. She delves into the emergence of Graph RAG for enhancing AI systems and discusses the future of graphs as memory for AI agents and in causal inference.