Document Classification and Data Extraction

Artificial Intelligence can improve document classification & data extraction.

There’s a wide range of solutions available today for document classification and data extraction from structured and semi-structured content and documents, such as databases, websites, or paper-based forms—all of which can be read by machines using templates or sets of predefined or custom rules. However, many businesses such as real estate, healthcare, energy, and others for legal, regulatory, or historical reasons still rely heavily on complex unstructured documents. These are inconsistent in layout or form or contain key information in English-language sentences, paragraphs, or randomly throughout the documents, making them virtually impossible for machines to understand. Classifying and extracting unstructured data from documents like deeds, property descriptions, health care forms, legal contracts, and conveyance transactions is a costly and time-consuming process, especially when a company relies on hundreds of thousands or even millions of these documents. It’s a labor-intensive activity that is expensive, slow, and prone to errors that adversely affect business processes and customer service.

Axis Technical Group offers a far better choice with an enterprise solution for document classification and data extraction from unstructured content. Using proprietary algorithms based on Artificial Intelligence, including those used to perform Natural Language Processing (NLP), Axis reads and extracts data from sentences, paragraphs, or entire pages written in natural English. The result is unparalleled data extraction results that minimize or eliminate time-consuming and expensive manual re-keying processes—and far exceed the results obtained from competing systems, which are typically complex, cost-prohibitive, and ineffective.

Paper documents are scanned, and the resulting digital files such as PDFs or TIFs are converted into searchable electronic documents using optical character recognition (OCR) technology. Users highlight relevant portions of digitized documents to “train” the extraction engine on what to look for in batches of documents. Test runs help assess the accuracy of the document classification and data extraction. A first pass by the classification/extraction engine typically produces a high level of accuracy; subsequent passes can be conducted until the client is satisfied with the quality and accuracy of the data extraction. Our solution offers numerous benefits:

  • Secure Microsoft Azure cloud
  • Subscription service – no hardware or software
  • Pay for what you use
  • 1000’s of Document Types already trained
  • Financial document processing SMEs
  • No document too difficult to manage