Retrieval Augmented Generation (RAG) systems excel at semantic search and knowledge retrieval but face challenges in implementing nuanced access controls, particularly when dealing with sensitive data. As organizations scale RAG systems to serve multiple business units with varying data sensitivity requirements, they encounter compliance issues, especially under regulations like GDPR and CCPA. Traditional solutions like bulk permission checks and iterative filtering are inefficient and inadequate, highlighting the need for in-database authorization, where authorization logic is integrated directly into the database query process. This approach ensures faster response times and a simpler architecture by treating authorization as a first-class concern, thereby eliminating the authorization gap and allowing for efficient, secure data access. A practical implementation demonstrates this by using a RAG chatbot with integrated authorization logic, leveraging Oso Cloud and SQLAlchemy to manage complex access control models while maintaining query performance and security.