Accelerating custom entity recognition with Claude tool use in Amazon Bedrock

This article demonstrates how to use Claude Tool use (function calling) in Amazon Bedrock to extract custom entities from documents like driver's licenses without traditional model training.

• Claude Tool use enables LLMs to invoke external functions for structured data extraction
• Serverless architecture uses S3, Lambda, Bedrock, and CloudWatch for document processing
• S3 upload triggers Lambda function that sends images to Claude for entity extraction
• Define tool schemas with JSON to specify required fields and data types
• Lambda function encodes images in base64 and invokes Claude via Bedrock API
• Configure S3 event notifications to automatically trigger Lambda on file upload
• Supports JPEG, PNG, WebP formats; max 20MB, 4096x4096 pixels recommended
• CloudWatch logs display extracted data in structured tool_use format
• Implement error handling, security best practices, and performance optimization

This solution provides scalable, cost-effective document processing without complex ML model setup or maintenance.