Uploaded February 2026 | Updated September 2026, 2 weeks ago
Building enterprise-ready AI requires ensuring users can only augment prompts with data they're authorized to access. Relationship-based access control (ReBAC) is particularly well-suited for fine-grained authorization in Retrieval-Augmented Generation (RAG) because it makes decisions based on relationships between objects, offering more precise control compared to traditional models like RBAC and ABAC.
This talk covers how ReBAC systems can safeguard sensitive data in RAG pipelines. We'll start with why Authorization is critical for RAG pipelines, and how Google Zanzibar achieves this with ReBAC. We'll then illustrate how pre-filtering vector database queries with a list of authorized object IDs can improve efficiency & security. The talk will also include a demo implementing fine-grained authorization for RAG using Pinecone, Langchain, OpenAI, and SpiceDB.
Building enterprise-ready AI requires ensuring users can only augment prompts with data they're authorized to access. Relationship-based access control (ReBAC) is particularly well-suited for fine-grained authorization in Retrieval-Augmented Generation (RAG) because it makes decisions based on relationships between objects, offering more precise control compared to traditional models like RBAC and ABAC.
This talk covers how ReBAC systems can safeguard sensitive data in RAG pipelines. We'll start with why Authorization is critical for RAG pipelines, and how Google Zanzibar achieves this with ReBAC. We'll then illustrate how pre-filtering vector database queries with a list of authorized object IDs can improve efficiency & security. The talk will also include a demo implementing fine-grained authorization for RAG using Pinecone, Langchain, OpenAI, and SpiceDB.
