Redis launches context architecture to solve the memory problem plaguing enterprise AI agents
Redis unveiled Iris, a context and memory platform designed to fix the structural data problem causing production AI agents to fail. The platform addresses the scale mismatch between agent-generated data requests and existing retrieval infrastructure built for human-scale queries. With components including Context Retriever, Agent Memory, and Redis Data Integration, the launch signals a broader industry shift away from traditional RAG approaches.