Redis Iris context engine

Redis Iris is a suite of managed and self-managed services for agent memory, semantic caching, and governed data access.

Give your AI agents the context layer they need to reliably act on business data.

Redis Iris eliminates the infrastructure burden of building context-aware AI agents: persistent memory, semantic caching, governed data access, and live data sync, fully managed on Redis Cloud or self-managed on your own infrastructure.

Concepts

What happens when an agent asks Redis Iris for context

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Agent Memory

Persistent short-term and long-term memory across agent interactions

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LangCache

Semantic caching to reduce LLM costs and improve response times

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Context Retriever

Governed, schema-first data access tools for agents

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What is Redis Iris?

Redis Iris is a production-ready context engine for AI agents that:

  • Reduces LLM costs: Semantic caching returns cached responses for similar queries in milliseconds
  • Adds persistent memory: Agents remember past interactions and user preferences across sessions
  • Structures business data access: Context Retriever generates governed tools agents can safely call at runtime
  • Keeps data fresh: Data Integration streams live changes from relational databases into Redis within seconds
  • Deploys your way: All four services are available fully managed on Redis Cloud or self-managed on your own infrastructure, via REST API

Why use Redis Iris?

For AI applications

  • Agents that remember context across sessions and users
  • Faster responses and lower costs through semantic caching
  • Reliable, structured access to live business data
  • No stale data: near real-time sync from your source databases

For developers

  • Four services, fully managed on Redis Cloud or self-managed on your own infrastructure
  • Python and JavaScript SDKs and REST APIs for all services
  • Define your data model once, reuse it across all agents
  • No database setup required on Redis Cloud

Next steps

Learn how Redis Iris works, from the agent request to where each kind of context lives.

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