• Comparing Elasticsearch vs. OpenSearch. Read more here.
• Read more about LangCache, our new managed semantic caching service, and get started today for free.
• Get hands-on building AI in Redis University: Vector Search with RedisVL & Build a RAG Chatbot.
• Redis now has a dedicated template on Railway designed to make deployment simple. Check it out here.

Last month, we acquired Featureform, an open source feature store. Adding Featureform to our platform unlocks a new level of performance and clarity for AI builders everywhere.

AI agents can’t operate purely on unstructured data or LLM context — they need reliable, real-time structured signals (user history, metrics, relational data). Featureform’s framework helps define, version, and serve features seamlessly across batch and streaming workflows, with observability and correctness built in.

With Redis + Featureform, you can:

If you’re building agents that need context, not just words, this opens up a new level of performance and reliability.

As AI systems grow more complex, one thing is clear: they’re only as smart as their memory. O’Reilly’s latest report, “Managing Memory for AI Agents,” breaks down why memory has become the missing piece for intelligent systems—and what builders and decision-makers should know.

You’ll learn:

The takeaway: without memory, AI can’t deliver on its promise. This Redis-sponsored report explores how to build AI systems that scale seamlessly and adapt to what’s next.