Making AI Make Sense with Graphs: Context, Connections, and GraphRAG with Amy Hodler

In this episode, we explore why graph technology is becoming foundational to the next wave of AI—especially as systems grow more complex and context becomes essential. Our guest is Amy Hodler, founder of GraphGeeks and a longtime leader in connected data, AI strategy, and graph analytics. Amy takes us on a deep dive into how graphs offer a more natural, human-centered way to model data—focusing not just on what things are, but how they relate. We talk about GraphRAG, the blend of graph structures with retrieval-augmented generation, and how it’s giving AI systems a richer, more contextual backbone. Whether you're an ML engineer, a data scientist, or just graph-curious, this conversation is full of insight into why relationships are the key to relevance in AI. Key Topics Covered: Why graphs are a natural fit for how humans think and make decisions The evolution of GraphRAG and why it matters for building smarter LLM systems How context-rich graphs improve AI explainability, fairness, and performance Where graphs are gaining traction: cybersecurity, legal review, systems engineering The growing importance of entity resolution and building high-quality graphs Best practices for getting started with GraphRAG—and common pitfalls to avoid Emerging trends: multimodal graph systems, agentic AI workflows, and graph-vectors hybrids Why AI can’t solve every problem—and what to watch out for in the age of “AI snake oil” Memorable Outtakes 💬 “Graphs aren’t just about data points. They’re about what makes those points meaningful—relationships.” 💬 “If you care about context, you should care about graphs.” 💬 “GraphRAG isn’t just another buzzword. It’s how we bring structure and context into generation.” 💬 “AI without context is guessing. Graphs help it make sense.” 🔗 References & Resources - Amy’s LinkedIn: https://www.linkedin.com/in/amyhodler/ - Amy’s Twitter/X: https://x.com/amyhodler - GraphGeeks’ Website: https://www.graphgeeks.org/ - GraphGeeks’ LinkedIn: https://www.linkedin.com/company/graphgeeks/ - Graph Algorithms: Practical Examples in Apache Spark and Neo4j: https://www.amazon.com/Graph-Algorithms-Practical-Examples-Apache/dp/1492047686 - David Hughes’ LinkedIn: https://www.linkedin.com/in/dahugh/overlay/about-this-profile/ - Amy’s ODSC East 2025 Session, Advancing GraphRAG: Text, Images, and Audio for Multimodal Intelligence: https://odsc.com/speakers/advancing-graphrag-text-images-and-audio-for-multimodal-intelligence/ - Blog, What is GraphRAG? An In-Depth Look at This Graph-Based Tool: https://opendatascience.com/what-is-graphrag-an-in-depth-look-at-this-graph-based-tool/ - AI Snake Oil: What Artificial Intelligence Can Do, What It Can’t, and How to Tell the Difference: https://www.amazon.com/Snake-Oil-Artificial-Intelligence-Difference/dp/069124913X This episode was sponsored by: 🎤 ODSC East 2025 – The Leading AI Builders Conference – https://odsc.com/boston/ Join us from May 13th to 15th in Boston for hands-on workshops, training sessions, and cutting-edge AI talks covering generative AI, LLMOps, and AI-driven automation. 🔥 Use the exclusive code ODSCPodcast for an additional 10% off any ticket type!