Redis Iris context engine

Deploy and operate Redis Iris context engine services.

Redis Iris

LangCache, Agent Memory, and Context Retriever are currently available in preview. Features and behavior are subject to change.

Redis Iris context engine provides managed and self-managed services for building AI applications with persistent memory, semantic caching, and governed access to business data.

Use this section to deploy, configure, and operate Redis Iris services. Developer guides and API integration documentation remain under Develop with Redis.

Redis Agent Memory

Create and manage a service on Redis Cloud or deploy it on your own infrastructure

Learn more →

Redis Context Retriever

Create and manage governed retrieval tools for AI agents

Learn more →

LangCache

Create, configure, and monitor semantic caches for AI applications

Learn more →

Deployment options

Redis Iris services are available as managed services on Redis Cloud. All Redis Iris services are also available for self-managed deployment.

Redis Cloud

Create and manage Redis Iris services through the Redis Cloud console without deploying the supporting infrastructure yourself.

Self-managed

Deploy Redis Iris services on Kubernetes when you need to operate them on your own infrastructure.

	Products	Version
	Develop with Redis Clients, data types, programmability, and Redis for AI. RedisVL is listed separately.
	Libraries and tools Client libraries, observability, and cloud integrations. Redis Data Integration is listed separately.
	RedisVL
	Redis Software
	Redis Cloud
	Redis for Kubernetes
	Redis Open Source
	Redis Iris context engine
	Redis Feature Form
	Redis Insight
	Redis Data Integration
	Glossary
	Command reference

Redis Iris context engine

Deployment options

Redis Cloud

Self-managed

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