What is AWS Textract; A new world with Intelligent Document Processing.

Processing Large-Scale Documents: A Challenge

Many organizations have scanned and handwritten documents, including financial institutions, healthcare, manufacturing, and other businesses. Imagine you have an archive of copies from which you would like to extract data; you can have a human read the document and then key all the values into a processing application or another document for easy processing.

Another approach is using rule-based formatting with an Optical Character Recognition(OCR) system to extract data from documents. Organizations have utilized these approaches to process and derive insights from records; however, they have lived in a world with many document processing challenges.

Humans have spent productive hours applying domain knowledge to extract insights from documents, perform mundane data entry and document review tasks, and spent thousands of dollars on provisioning infrastructure that handles associated processing workflows. It is costly for organizations to hire resources, pay for the infrastructure and continually manage the implementation of these services.

This article will explain what Amazon Textract is and how it can benefit you and solve the challenges mentioned above in document processing.

A new world with Intelligent Document Processing (IDP)

What is Textract

Firstly, the process of extracting data from documents, such as receipts, resumes, tax forms, scanned photos, etc., for subsequent processing is called intelligent document processing.

Amazon Textract presents a way of extracting handwritten & printed text in forms, tables, pages from images, and PDF documents without any manual effort. It provides a serverless API that enables quick document management and scalability to millions of documents. It comes with a pre-trained model and provides APIs where you can send your documents in PDF or image format and get a response as text/tables, key/value pairs, and a confidence score.

Intelligent Document Processing with Textract

Amazon Textract supports many file formats — such as PNG, JPEG, and PDF files, and uses cases. Several use cases in IDP can leverage the power of AWS Textract for automation; some examples are below.

Insurance Industry

The insurance industry processes quite a lot of time-consuming documents, and the process is error-prone. Therefore, the industry would benefit from IDP significantly to automate data extraction for frequent use cases, including claims input, policy servicing, quotes, and payments.

A typical IDP process for an insurance company can be to use AWS Textract to extract data from scanned documents in claim settlements, issuing policies, etc., for further insights processing.

Legal Industry

While working on cases, lawyers frequently become bogged down with paperwork. Most legal documents are lengthy and extensive, whether for the clients, the ongoing litigation, or even reference material to prepare for a case.

For example, It might take hours for attorneys to attempt to annotate Contract documents. Leveraging AWS Textract, the IDP process effectively summarizes and extracts information from the contract agreements, data storage, and digitization of existing contractual information, thus automating a large chunk of legal firms’ document processing workflows.

Financial Industry

The finance industry is another industry that processes large amounts of documents, and its operations are document-centric. With Textract, financial firms can quickly process loan, mortgage, and commercial debt applications by accurately extracting crucial business information from corresponding financial forms. They can also use IDP to automate processes such as the KYC process (Know-your-customer), Anti-money laundering compliance applications.

AI Process Automation

From the examples above, you would understand that several industries leverage the IDP to automate document processing and the data or text extraction done with Textract. However, this is only a part of the IDP- data capture/data extraction. Add AI Process Automation to the workflow to automate insight generations, classifications, and recommendations.

Transformer models have changed how we work with text data, and state-of-the-art pre-trained models are available for easy access to build AI applications. Leveraging on this, once the data extraction occurs, users will be able to do other tasks with AI embedded in the workflow — such as Named Entity Recognition, Classifications, Text Summarization, Question Answering, etc. Thus, companies can build complex AI workflows that solve business needs, automate processes, and store information for easy retrieval.

What we are doing at Mantium

At Mantium, We are building a feature that allows users to build AI applications in Mantium that uses all the Textract services to create workflows to power intelligent document processing.

Sign up for a Beta-Access to be a part of the new world we are leading in AI Process Automation.

You can also join our growing community on Discord; we’d be happy to answer your questions and help you in your building process.