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The IDP Well-Architected Custom Lens is intended for all AWS customers who use AWS to run intelligent document processing (IDP) solutions and are searching for guidance on how to build a secure, efficient, and reliable IDP solution on AWS. This post focuses on the Reliability pillar of the IDP solution.
Intelligent document processing (IDP) with AWS helps automate information extraction from documents of different types and formats, quickly and with high accuracy, without the need for machine learning (ML) skills. This is where IDP on AWS comes in. These challenges are only magnified as teams deal with large document volumes.
Document processing has witnessed significant advancements with the advent of Intelligent Document Processing (IDP). With IDP, businesses can transform unstructured data from various document types into structured, actionable insights, dramatically enhancing efficiency and reducing manual efforts.
The global intelligent document processing (IDP) market size was valued at $1,285 million in 2022 and is projected to reach $7,874 million by 2028 ( source ). We specifically used the Rhubarb Python framework to extract JSON schema -based data from the documents.
With Intelligent Document Processing (IDP) leveraging artificial intelligence (AI), the task of extracting data from large amounts of documents with differing types and structures becomes efficient and accurate. The following diagram is how we visualize these IDP phases. marketing materials, newspaper clips, and the list goes on.
The Apache Tika open-source Python library is used for data extraction from word documents. Please refer to TextractAsync , an IDP CDK construct that abstracts the invocation of the Amazon Textract Async API, handling Amazon Simple Notification Service (Amazon SNS) messages and workflow processing to accelerate your development.
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