Technological development of functionalities with convolutional neural networks for intelligent document management

Abstract

In the current highly digitized business landscape, efficient document management is crucial for increasing productivity and optimizing organizational processes. This need has been identified in this document, and an enhanced product named Infopoint, an enterprise content management software has been improved to provide intelligent document management through the implementation of advanced automation and artificial intelligence technologies. In document management, numerous processes are still manually executed, leading to errors and delays due to the burden of repetitive tasks. Manual management also causes internal delays and impacts interactions with clients, suppliers, and regulatory entities. Manual document searches consume valuable time and can result in unnecessary costs for the company. Infopoint addresses these challenges by incorporating automation features, particularly leveraging convolutional neural networks. This approach optimizes the functionality of incoming correspondence, reducing processing time by 29 %, on average. It also facilitates text and content searches within PDF documents, decreasing the average search time by 41 %. This article highlights how this improvement significantly reduces the time spent on correspondence management and information retrieval.