Building the future Architecting AI Agents with AWS, LlamaIndex and Redis

About

This session breaks down how to build AI agents with AWS, LlamaIndex, and Redis using the retrieval-augmented generation (RAG) framework. Learn how embeddings, knowledge bases, and orchestration tools improve AI performance. Watch a demo showing how Redis provides faster retrieval, smarter caching, and seamless document management with Amazon Bedrock and LlamaIndex.

Link to the GitHub repository: https://github.com/redis-developer/agentic-rag

Key topics

1. Learn how AI agents break tasks into efficient, high-performing components
2. Design agentic systems that cut costs and reduce lag
3. Explore tools and frameworks that simplify AI agent development
4. See how Redis provides real-time AI with vector search and semantic caching