☕️ Build production-ready RAG workflows on AWS

Caching + vector storage in one managed platform, plus a step-by-step RAG agent build.  ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌

Read online         Today's edition is sponsored by AWS Marketplace, on something a lot of you are building right now: production RAG.   Here's the problem nobody warns you about.   To ship a real RAG app, most teams end up running two databases: a cache (for speed) and a separate vector store (for retrieval), plus the glue code to keep them in sync. Two systems to provision, monitor, and keep in sync and to debug at 2am.   There's a simpler stack.   Redis Cloud on AWS combines caching and vector storage in one managed platform, so you get low-latency retrieval without running two systems. It runs on AWS, connects to your AWS workloads, and bills pay-as-you-go through your AWS account. And it's built for production RAG from day one.     Get started in AWS Marketplace →     Build a RAG agent with Redis Cloud and Amazon Bedrock   You don't need a migration project to try it. The short path:   Subscribe to Redis Cloud in AWS Marketplace and start the 14-day free trial, procurement and billing stay on your AWS account. Create a vector index in Redis Cloud and connect it as the vector store for an Amazon Bedrock Knowledge Base, Amazon Bedrock ingests your documents and stores the embeddings in Redis. Associate the Knowledge Base with an Amazon Bedrock agent for contextually aware responses backed by low-latency retrieval.   That's it. One platform for caching and vectors, one bill, one thing to operate.   Why it’s worth a look:   Redis Cloud keeps caching and vector search in one place, works with Amazon Bedrock, and scales pay-as-you-go through AWS Marketplace.   If you're wiring up RAG this quarter, that's one less database to provision, monitor, and keep in sync.   Accelerate generative AI on AWS →     Louis, Laura, and the ☕️ Techpresso team.     Update your email preferences or unsubscribe here © 2026 ☕️ Techpresso 228 Park Ave S, #29976, New York, New York 10003, United States