Real-time feature store

Your agents aren't failing. Their context is.

See how we fix it

Platform

Platform

Redis IrisReal-time context for agents Redis LangCacheSave on tokens for common questions Redis Context RetrieverLeverage context from anywhere Redis Agent MemoryAgentic memory for consistent experiences Redis Data IntegrationCDC across your structured data Redis FlexMore data, more speed, less cost CachingSub-ms read/write at scale StreamingEvent-driven messaging & data pipelines Session managementFast, persistent storage for sessions SearchSearch & query for structured data Feature storeReal-time ML feature pipeline for apps & agents

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Deploy

Redis CloudFully managed, fully flexible Redis SoftwareOn-prem Redis open source frameworkRedis 8.6 PricingLet’s talk numbers Redis on AWSBuy with cloud commits Azure Managed RedisMicrosoft-supported Redis Redis on Google CloudRedis from the marketplace

Tools

Redis InsightUI to visualize, query, & debug RIOTGet data into Redis from anywhere Client librariesPython, Node, Java, Go, .Net, & more SDKsConnect Redis to your apps

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Solutions

AI & ML Apps

Scale agent & agentic systems Everything you need to be successful RAGUnderstand how Redis powers RAG Semantic searchRight answers, right now MLLeverage your features, fast Token optimizationAll the AI without all the cost

Core Workloads

Fraud detectionStop fraud, protect customers Real-time decisionsAct on data in real time Caching & performanceOur bread & butter Real-time messagingStreams at the speed of thought Session managementConsistent experiences everywhere LeaderboardsKnow who’s winning

Industries

Financial services E-commerce & retail Gaming Healthcare Telco

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Docs

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Learning

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Resources

Customers

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Resource Center

Events & webinars Blog Videos Glossary Resources Architecture Diagrams Demo Center

Resource Center

Events & webinars Blog Videos Glossary Resources Architecture Diagrams Demo Center

A demonstration on how Redis could be used as a real-time feature store for AI/ML workloads.