Your agents aren't failing. Their context is.
GPUs train the model. But intelligence comes from context.
They forget between sessions—and don’t always have the right context at the right time.
Without the right infrastructure:
The hard part isn’t generating tokens. It’s delivering the right context, in real time, every time.
Redis powers the systems that give AI the context it needs:
We would not have been able to scale ChatGPT without Redis.”
Using Redis, Bank of America has built fast, high-quality digital experiences for their clients at scale, from use cases like caching and session management, to event streaming and AI infrastructure."
We’re using Redis Cloud for everything persistent in OpenGPTs, including as a vector store for retrieval and a database to store messages and agent configurations. The fact that you can do all of those in one database from Redis is really appealing.”
Better answers and more current real-time information with up to 2.35X better performance with the Xeon 6 and Redis."
A closer look into the real-time context engine
Unified context makes everything easier. Agents get better memory, personalization gets faster, and chatbots become truly useful assistants.
Context engineering & agent memory with LangGraph & Redis
Read our guide to get example architectures, practical advice, and a deep dive into building scalable AI apps.
Executive lunch: Unifying & scaling AI infra @ NVIDIA GTC
Skip the conference food and join us for a sit down lunch. Exchange lessons learned with other leaders navigating the same challenges, and compare what’s working, what’s brittle, and what actually scales.
Speak to a Redis expert and learn more about enterprise-grade Redis today.
