We would not have been able to scale ChatGPT without Redis.”
AI runs on NVIDIA. Real-time context runs on Redis.
GPUs train the model. But intelligence comes from context.
LLMs are stateless.
They forget between sessions—and don’t always have the right context at the right time.
Without the right infrastructure:
- Context gets lost
- Outputs become inconsistent
- Hallucinations rates climb
- Stacks become slow, brittle, and hard to scale
The hard part isn’t generating tokens. It’s delivering the right context, in real time, every time.
Meet the real-time context engine
Redis powers the systems that give AI the context it needs:
- Long- and short-term agent memory
- Real-time vector retrieval
- Sub-10ms semantic caching
- Hybrid search across structured and unstructured data
- Stateful conversations at scale
Built for production. Trusted by the world’s most demanding apps.
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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.”
Harrison ChaseCEO
Read moreBetter answers and more current real-time information with up to 2.35X better performance with the Xeon 6 and Redis."
video
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.
guide
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.
event
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.
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