Optical Character Recognition

Optical character recognition (OCR) technology is designed to convert images of text into digital characters, or data. OCR technology is often embedded into hardware devices like printers, document scanners, web scanners, etc., available within desktop software like PDF readers, or into intelligent automation systems that help to store, process, and manage digital documents.

In the 1970s, one of today’s pioneering minds on artificial intelligence helped to usher in the next age of OCR innovation. Currently Google’s Chief Futurist, Ray Kurzweil, developed a software product that could recognize text images in any font. Originally combined with text-to-speech synthesis to enable computers to read printed material to the blind, Kurzweil’s software led to the possibility of converting printed pages of all kinds to computer text. This allowed for the extraction of raw character or ASCII data from a page.

But OCR (Optical Character Recognition) software has come a long way since its original role. Today, intelligent data capture solutions can convert text images to digital characters and THEN parse through that information to identify data that is actionable or relevant to a process.

Problems Solved

Intelligence =Flexibility, Scalability and Easy of Use

Today, excitement and interest in robotic process automation and artificial intelligence has sparked the notion of a revolution in process innovation. In reality, however, this revolution is the latest stage in a number of intelligent automation technology evolutions.

OCR remains a key solution to solving the problem of ‘big data’ in the form of unstructured documents and images that make up the bulk of the digital information in the world.

To help manage, organize and derive meaning from unstructured data, intelligent OCR technology can automate what otherwise requires a human and a keyboard.

Modern intelligent data capture solutions don’t require users to manually create templates to read different documents and extract data. These systems employ machine learning to self-learn new document types by emulating user guidance/validation performed on a single new sample — progressively building a knowledge base to compare against new documents.

Artsyl Solutions

Artsyl Intelligent Capture Solutions Focus on Flexibility, Scalability and Ease of Use

Artsyl’s docAlpha digital transformation platform provides intelligent data capture, data validation, workflow automation, and ERP integration or ECM integration, to support intelligent capture and end-to-end process automation.

Along with machine learning as the primary data extraction method, the Artsyl intelligent process automation platform employs powerful OCR technology to automatically map all data from physical documents into digital files.

The docAlpha knowledge base gathers the combined intelligence of all your docAlpha users to continuously improve and expand upon the types of documents it can read and process automatically.

The docAlpha platform delivers:

  • Self-learning intelligent data extraction
  • Automatic document classification and separation
  • Machine print, hand-print text and check mark recognition
  • Barcode recognition
  • Automatic redaction

docAlpha applies intelligent automation to systematically identify, sort and classify documents, allowing users to batch process physical documents without pre-sorting or using page separators or barcodes. It can read and extract data from printed documents as well as from hand-printed documents and identify checkmarks, with support for a variety of OCR/ICR/OMR engines.

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