Our enterprise-ready solution for automatic text extraction employs computer vision, text recognition, optical character recognition (OCR), machine learning, and deep learning technologies. Any picture or digital document may be processed using the User Interface or through the Batch Process. Integration with third-party systems such as ERP, bookkeeping, and RPA enables complete business process automation. Such solutions, subject to permission or review, can be incorporated into current workflows for quick processing. Because it is automated, it is possible to provide additional benefits such as rule-based notifications, alerts, reminders, and text translation to offer users real-time information.
Many industries employ digital document text extraction and processing technologies, which leads to workflow automation and process reengineering. The legal business, which is primarily reliant on paper documents, may profit greatly from the ease and convenience of such new solutions. This solution aids in the efficiency of enterprises that handle a huge volume of papers. Even though they are of the same kind, each document has a unique format (such as an invoice). It is essential that such a system can accommodate these disparities.
Technology Used
Brief / Introduction About vDigiDocr
Manual flow in which the documents are scanned via UI where the user marks the boundaries of the data to be retrieved from the document. To be used for ad hoc document processing with high accuracy.
Semi-Automatic flow in which templates are pre-defined with the boundaries marked for the list of data fields to be retrieved from the document of specific format. Any document of that format will get auto-scanned via UI or batch process using the same template and the extracted Output will be displayed on the UI or saved into a db or csv file for further processing. To be used where images/documents of the same format to be processed repeatedly with high accuracy.
Automatic flow uses machine and deep learning algorithms to scan the documents via UI or batch process. It auto marks the boundaries of the data fields of interest and retrieves the data. It uses a model to auto mark the boundaries. Model is pre-traned with the relevant documents so that it can apply on any new document of any format. More the training, better is the accuracy of data extraction. Deep Learning Model runs on any Cloud platform like AWS or Google and is trained under supervision.
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