Build a production-grade Agentic RAG system using AuthZed Cloud

Jake Moshenko, CEO of AuthZed, predicts that Agentic Retrieval-Augmented Generation (RAG) will become the standard approach in enterprise applications as AI agents are increasingly adopted. A blog post demonstrates how to construct an Agentic RAG system using AuthZed Cloud, highlighting the complexities of real-world document sharing and the inefficiency of traditional role-based access control systems. The demo employs Weaviate as a vector database, the OpenAI API for language model processing, and LangChain-SpiceDB integration for fine-grained permissions, with SpiceDB ensuring deterministic authorization checks. The system's architecture incorporates a four-node LangGraph pipeline where the authorization process is integral and cannot be bypassed, demonstrating the importance of robust access control in AI systems to prevent security breaches. SpiceDB's minimal schema facilitates department-based access, cross-department grants, and public documents, and its CheckBulkPermissions API efficiently handles multiple permission checks. The blog underscores the importance of not relying on the client-side for access control, especially with AI agents, and invites users to explore AuthZed Cloud for scalable authorization infrastructure.

Use this post, company, and trend context to find content marketing opportunities, perform competitive analysis, or address product feature gaps via the Plushcap MCP server or the Plushcap API.