Jesús Barrasa

This talk explores the integration of knowledge graphs and Large Language Models (LLMs) for building robust AI applications, specifically focusing on the Graph RAG architecture. It highlights how ontologies, as formal, implementation-agnostic schemas, can significantly enhance knowledge graph creation and retrieval strategies, leading to more grounded and accurate AI responses. The core thesis is that a model-driven approach using ontologies provides practical wins by improving data quality and enabling dynamic retriever behavior.