Redis for AI on AWS

What you'll learn

• Adopting AI at scale isn’t just about choosing a model. It’s about building systems that can deliver speed, accuracy, and reliability under real workloads.

  Teams commonly run into issues like slow and expensive large language models, hallucinated outputs, long time to value, and tech stacks that were never designed for high-throughput, low-latency AI workloads. Add in the complexity of rethinking data pipelines, managing short- and long-term memory, and implementing agentic memory, and progress stalls fast.

  To build AI applications that actually perform in production, you need a unified, high-performance data platform designed for real-time responsiveness and intelligent memory.

  Redis goes far beyond caching. It acts as a real-time context engine that gathers, syncs, and serves the data your AI applications need to respond accurately and at speed. That’s why 42.9% of developers rely on Redis for the memory, data storage, flexibility, and reliability required to bring production-grade AI applications to life.

  Download the guide to learn how Redis on AWS powers real-time AI from infrastructure to real-world use cases, so you can build smarter, faster, and more resilient AI applications.