Protecting Sensitive Data in the Age of Generative AI by Alex Soto @ Spring I/O 2026

This session at Spring I/O 2026 focuses on the intersection of Generative AI and Retrieval-Augmented Generation (RAG) and the critical issue of protecting sensitive information as powerful large language models (LLMs) are connected to private data. The speaker discusses the potential for information to unintentionally leak through vector embeddings and presents new algorithms and architectures designed to safeguard this data. Attendees learn about secure design patterns for implementing RAG systems while ensuring compliance and performance. The talk also highlights emerging tools and frameworks that facilitate secure AI development, aiming to empower organizations to innovate responsibly with their valuable data.