Retrieval-augmented generation (RAG) offers advantages for enterprise AI chatbots but presents security challenges, particularly with role-based access control. Sensitive data leakage can occur if permissions are not properly managed. The combination of Realm's enterprise connectors and ApertureDB's graph-vector storage enables efficient and secure access control, ensuring proper document permissions. This integration allows for scalable, real-time access control and enhances chatbot security, reducing management overhead and improving retrieval quality.
Table of contents
Use Realm and ApertureDB To Build Secure RAG ApplicationsIntroductionChallenges In Building A Secure ChatbotWhy Choosing The Right Vector Database Matters How ApertureDB’s Graph-Vector Combination Simplifies Secure RAG PipelinesBootstrapping the Enterprise ACL GraphIngesting Users & Files into ApertureDBEnforcing Access Control During RetrievalConclusionAbout Realm LabsAbout ApertureDataAuthors42 Impressions