Anthony is recognized as a thought leader and primary innovator of products, solutions, and technologies for the intelligent capture, RPA, BPM, BI and mobile markets. ABBYY is an innovator and leader in artificial intelligence (Al) technology including machine learning and natural language processing that helps organizations better understand and drive context and outcomes from their data. The company sets a goal to grow and strengthen its leadership positions by satisfying the ever-increasing demand for AI-enabled products and solutions. ABBYY has been developing semantic and AI technologies for many years. Thousands of organizations from over 200 countries and regions have chosen ABBYY solutions that transform documents into business value by capturing information in any format.
Whether you're aware of it or not, artificial intelligence (AI) has a ubiquitous presence in our lives today – think the personalised playlists on Spotify or the'Recommended for you' lists on Netflix, both of which use AI to curate a selection tailored just for you. Now its presence is being felt in the area of document management, with AI and cognitive computing set to revolutionise the ways in which we store, archive, process and extract information. Here are 5 ways AI is transforming document management systems . Automatic classification and processing - While OCR (optical character recognition) technology allows for text recognition, AI takes this a step further by being able to "read" the information on that document, classify it correctly and automate workflows based on that classification – all at a fraction of the speed a human could. While the system is initially guided by a set of rules, its identification and processing capabilities continue to improve using machine learning, meaning it is able to learn from repeated exposure to documents, as well as from the actions taken by employees upon those documents.
Working with an enormous amount of text data is always hectic and time-consuming. Hence, many companies and organisations rely on Information Extraction techniques to automate manual work with intelligent algorithms. Information extraction can reduce human effort, reduce expenses, and make the process less error-prone and more efficient. It will also cover use-cases, challenges and discuss how to set up information extraction NLP workflows for your business. For example, consider we're going through a company's financial information from a few documents.
This article will take you through what digital transformations are, what drives it, how to aid successful digital transformations, how AI and deep learning can help, the challenges you might face in implementation and how to work around them. We will also talk about what the current pace of technological growth means for the future of work and what we can do about the paranoia that goes along with increasing automation. While talking about singularity or Skynet taking over is not the point of this blog, it would be a little apathetic to not acknowledge the risks that come with acceleration in technological advancement. Have a data extraction problem in mind? Head over to Nanonets and start building models for free!
PO Matching is the process of connecting a purchase order (PO) issued by a client indicating types, quantities, and agreed prices for products/services to the invoice issued by a vendor for it's delivery. The goal of PO matching is to ensure timely vendor payments, correct accounting of costs and easy detection of fraudulent practices. PO matching involves several steps, including the receipt of invoice, capture of data, verification with purchase order, matching the parameters, and resolution based on various parameters. Invoice processing and PO matching are complex, time-consuming, and resource-intensive processes when performed manually, especially in scaled-up business activities. Even in departments where there is digitization of information in the form of Enterprise Resource Planning (ERP) applications, a significant amount of human labour is required; from the time an invoice is raised or received to its entry into the ERP application, accounts payable personnel perform a seemingly endless list of chores.