Enterprise data is fragmented across dozens of systems, resulting in agents that fail in production because their context is stale, slow, and impossible to navigate.
Introducing the real-time context engine, Redis Iris: the foundational layer that helps you build production-grade AI agents by turning scattered enterprise data into live, navigable, always-fresh context that gets better over time.
Built on four core pillars: Redis Context Retriever, Redis Search, Redis Data Integration (RDI), and Agent memory.

• Navigate fragmented data: Help agents find relevant information across enterprise systems without stitching together complex retrieval workflows.
• Respond without delay: Retrieve the right context fast enough to support real-time applications and decisions.
• Stay current: Keep context synchronized as source data changes, reducing responses based on stale information.
• Improve over time: Preserve interaction history, preferences, and relevant state so agents don’t start from scratch with every request.

See how Redis Iris brings retrieval, search, data integration, and memory together in a real-time context engine, and watch it solve these challenges