Optimizing AI Agent Performance: Bedrock Knowledge Base and Vector Retrieval

This article demonstrates how to optimize AI agents by separating data ingestion from retrieval using Amazon Bedrock's Knowledge Base and S3 Vectors storage. By pre-processing documents into embeddings, developers can dramatically reduce latency and operational costs while enabling semantic search across large historical datasets. This architecture pattern is crucial for building efficient, cost-effective AI applications that need rapid access to vast document repositories.