Your agents passed the demo. Now they have to survive production.
The models are good enough, but the real world is messy: users go off script, inputs are vague, and every handoff is another place for an agent to fail. Redis Iris gives your agents six composable capabilities for the memory, context, and messaging they need to be successful, in one context engine.
Talk to our team to map Redis Iris against your agent stack and find where to start.
Book an architecture review
What your teams get with Redis Iris
Production-ready agents from day one.
Fewer tokens, better outcomes
Route requests by meaning instead of wording, and reuse the answers and procedures that are stable. Agents stop re-running work they’ve already done.
Memory and context you can govern
Hierarchical memory that can forget what it shouldn’t keep, like PII, plus one permission-aware entry point to every connected context source, including your own MCP servers.
Agents you can explain and trust
Trace any outcome back to the skill, route, or memory behind it, and keep agent handoffs alive through dropped connections.
Bring your agent architecture
Let’s talk agent stacks, where you can save, and where we fit.
Everything you need to make the case
Benchmarks, customer stories, and docs to check our numbers against yours.
