Organizations process millions of documents daily, from insurance claims and invoices to legal contracts and medical records. While traditional optical character recognition (OCR) solutions extract text, they can’t understand context, relationships, or meaning embedded within complex documents. This limitation creates bottlenecks that require manual intervention, increasing processing time and costs while introducing potential errors.

Amazon Bedrock Data Automation (BDA), provides a unified API experience for extracting meaningful insights from multimodal content, including documents, images, videos, and audio files. Unlike traditional solutions that focus on text extraction, BDA understands document context, validates extracted data, and provides confidence scores for accuracy. BDA processes documents through a pipeline that automates complex tasks including document classification, extraction, normalization, and validation. When a document is submitted, BDA automatically splits it along logical boundaries, classifies each section into appropriate document types, and matches them to the correct processing blueprints. This intelligent routing removes the need for manual document sorting and orchestration of multiple AI models. The service supports a wide range of file formats, with support for up to 3,000 pages and 500 MB per API request, making it suitable for processing diverse document types at scale.