AWS Streamlines Intelligent Document Processing with New Programmatic Bedrock Framework

Amazon Web Services has introduced a new programmatic approach to Intelligent Document Processing (IDP). This solution integrates Amazon Bedrock Data Automation with the Strands SDK and Bedrock AgentCore to help developers build sophisticated AI agents. By using this framework, organizations can now automate the extraction of insights from complex documents without managing underlying servers.

IDP is a technology used to transform unstructured data from sources like invoices, contracts, and reports into structured, actionable information. For businesses, this means turning stacks of paper or digital PDFs into digital assets that a computer can understand. This automation reduces the need for manual data entry and helps teams find critical information in seconds rather than hours.

In a corporate setting, IDP can be applied to high-volume tasks such as financial auditing, legal document review, and educational reporting. For example, a business can use this solution to query dense academic reports to compare performance metrics across different regions. This technology effectively turns a static corporate archive into an interactive knowledge base that responds to natural language questions. [https://aws.amazon.com/bedrock/bda/]

The technical implementation utilizes Amazon Bedrock Data Automation as a unified parser for multimodal content. Unlike traditional methods that required complex "gluing" of services like Amazon Textract and AWS Lambda, this new approach handles text, tables, and visual elements natively. This streamlines the development of Retrieval-Augmented Generation workflows by providing a more direct path from ingestion to insight. [https://docs.aws.amazon.com/bedrock-agentcore/latest/devguide/what-is-bedrock-agentcore.html]

The Strands Agents SDK offers a model-driven approach where the large language model decides which tools to use based on the context of the task. This gives developers enterprise-grade flexibility while maintaining the ease of use found in managed services. Because the solution is deployed through Bedrock AgentCore, it provides a scalable environment for hosting custom agent logic without the overhead of managing EC2 instances.

To help developers begin, AWS has released a Jupyter notebook and a public GitHub repository with a complete implementation guide. The workflow includes secure file handling, identity management through IAM roles, and vector storage using Amazon OpenSearch Service. This programmatic framework is now available for organizations looking to scale their document analysis capabilities quickly and cost-effectively. [https://github.com/aws-samples/sample-for-amazon-bda-agents]