Build a Production RAG System on AWS Bedrock from Scratch

A complete hands-on guide to building Retrieval Augmented Generation on AWS Bedrock with pgvector,...

domenica 31 maggio 2026 New tab

6,585 words~30 min read

A complete hands-on guide to building Retrieval Augmented Generation on AWS Bedrock with pgvector, Guardrails, Prompt Management, Knowledge Bases, Evaluations and API Gateway

What You Will Build

A production-shaped Retrieval Augmented Generation (RAG) system on AWS Bedrock that a real engineering team could deploy. By the end of this guide you will have:

Documents ingested into Aurora Serverless v2 with pgvector via Titan Embeddings v2

Semantic search over your document corpus using HNSW vector indexing

Build a Production RAG System on AWS Bedrock from Scratch

Build a Production RAG System on AWS Bedrock from Scratch

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Related reading

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