Implement vector-prompt document classification using Amazon Bedrock
Amazon Web Services 1 week ago 37
Amazon Bedrock released a tutorial on building a multi-agent document classification system for insurance documents using Claude Haiku 4.5 and Titan Multimodal Embeddings, coordinated through the Strands Agents SDK. The solution uses three specialized agents—a Document Analysis Agent for text reasoning, a Vector Similarity Search Agent for visual pattern matching via FAISS, and a Validation Agent for quality assurance—working together to classify documents into POLICY, AFFIDAVIT, or MISCELLANEOUS categories. This approach improves accuracy over single-model systems by combining textual and visual analysis with built-in validation and confidence scoring.
