Anmol Sharma has developed ORAG, a platform designed to make internal organizational data accessible and usable for AI agents. The system addresses the challenge of providing AI with relevant, trustworthy, and permissioned context by implementing a Retrieval-Augmented Generation (RAG) pipeline and a Model Context Protocol (MCP) server. ORAG integrates with various data sources like Notion and GitHub, offers role-based access control, and aims to solve the context problem rather than the model itself. AI
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IMPACT Provides a standardized context layer for AI agents, potentially simplifying enterprise AI deployments.
RANK_REASON Developer releases a new platform for AI agent context management.
