Shows
AI Leadership Lab, by Ryan HeathThe Future of Data with Philip Rathle, Neo4J CTOIn this episode of AI Leadership Lab, host Ryan Heath sits down with Philip Rathle, Chief Technology Officer at Neo4j, to explore how graph databases are revolutionizing AI infrastructure and enterprise knowledge systems. Philip reveals why understanding the relationships between data points is more powerful than having all the facts, and how companies like Google built trillion-dollar businesses on graph algorithms. From explaining knowledge graphs in plain language to discussing how graph-based retrieval can make AI more trustworthy and explainable, this conversation delivers actionable insights for leaders seeking to build more effective AI systems.
2026-01-3021 min
Venture with GracePhilip Rathle, Neo4j CTO on GraphRAG, Graph Databases & AIPhilip Rathle is the Chief Technology Officer of Neo4j, where he has spent more than a decade helping transform the company from a niche on‑premise database into a leading global graph database and analytics platform used in modern AI and data-intensive applications. With over 25 years in enterprise data, he previously led Neo4j’s product organization, growing ARR from under seven figures to well into nine figures and expanding the portfolio into multiple cloud product lines, while building and leading large global product and engineering teams. Earlier in his career, Philip co-founded a customer data integration startup and...
2025-12-1657 min
The Data Exchange with Ben LoricaBuilding the Knowledge Layer Your Agents NeedThis episode features Philip Rathle, CTO of Neo4j, discussing the real-world state of Graph RAG and its journey from prototype to production in enterprise AI systems. Subscribe to the Gradient Flow Newsletter 📩 https://gradientflow.substack.com/Subscribe: Apple · Spotify · Overcast · Pocket Casts · AntennaPod · Podcast Addict · Amazon · RSS.Detailed show notes - with links to many...
2025-11-2647 min
DM RadioGraph for RAG, Networking and MoreHow can we make AI models more reliable and accurate? Tune in to this episode of DM Radio as we explore Retrieval-Augmented Generation (RAG) and Graph RAG—two innovative approaches that keep large language models grounded, relevant, and free from hallucinations. Host Eric Kavanaugh welcomes Philip Rathle, CTO of Neo4j, and Jon Brewton, CEO of data², to discuss how knowledge graphs enhance AI's ability to deliver precise, explainable, and context-aware insights.
2025-02-2053 min
The Ravit ShowThe GraphRAG ManifestoWhat is GraphRAG? It was great covering GraphSummit by Neo4j as Press, where I had the privilege of interviewing Philip Rathle, CTO at Neo4j on The Ravit Show.
— We had an in-depth discussion on GraphRAG and its potential to transform the future of AI and data management. Some of the key topics we covered were:
— The inspiration behind writing the GraphRAG Manifesto and why it's crucial for the AI community
— The distinct differences between GraphRAG and traditional RAG, and how these differences unlock new possibilities
— How knowledge graphs significantly improve the performance of generative AI systems
— The impact Gra...
2024-11-1514 min
AI Engineering PodcastEnhancing AI Retrieval with Knowledge Graphs: A Deep Dive into GraphRAGSummaryIn this episode of the AI Engineering podcast, Philip Rathle, CTO of Neo4J, talks about the intersection of knowledge graphs and AI retrieval systems, specifically Retrieval Augmented Generation (RAG). He delves into GraphRAG, a novel approach that combines knowledge graphs with vector-based similarity search to enhance generative AI models. Philip explains how GraphRAG works by integrating a graph database for structured data storage, providing more accurate and explainable AI responses, and addressing limitations of traditional retrieval systems. The conversation covers technical aspects such as data modeling, entity extraction, and ontology use cases, as well as the infrastructure...
2024-09-1059 min
Pondering AIRAGging on Graphs with Philip RathlePhilip Rathle traverses from knowledge graphs to LLMs and illustrates how loading the dice with GraphRAG enhances deterministic reasoning, explainability and agency. Philip explains why knowledge graphs are a natural fit for capturing data about real-world systems. Starting with Kevin Bacon, he identifies many ‘graphy’ problems confronting us today. Philip then describes how interconnected systems benefit from the dynamism and data network effects afforded by knowledge graphs. Next, Philip provides a primer on how Retrieval Augmented Generation (RAG) loads the dice for large language models (LLMs). He also differentiates between vector- and graph-based RAG. Along the way...
2024-08-2849 minThe Data Exchange with Ben LoricaSupercharging AI with GraphsPhilip Rathle, CTO of Neo4j, joins the podcast to discuss the rising popularity of graph-enhanced retrieval augmented generation (GraphRAG). He also discusses the potential impact of the new GQL graph query language standard. [Link to the demo that Philip showed.]Subscribe to the Gradient Flow Newsletter: https://gradientflow.substack.com/Subscribe: Apple • Spotify • Overcast • Pocket Casts • AntennaPod • Podcast Addict • Amazon • R...
2024-06-2743 minDM RadioA Graph for All SeasonsDiving deep into graph technology is one of the most meaningful steps towards data literacy. But there are so many methods to choose from! Philip Rathle, CTO of Neo4j, along with Lior Gavish, Co-Founder of Monte Carlo Data, help you navigate various graph models and the way they parallel what's happening in your database right here on DMRadio!
2024-06-0650 min