In each stage of document data integration, data science methods such as computer vision, text recognition, machine learning, and natural language processing increase human understanding of unstructured data.Intelligent Document Processing (IDP) is gaining popularity because it offers game-changing methods for automating data extraction projects that were previously difficult, if not impossible, to complete.<h3 id="what-has-changed-recently-in-document-processing">What Has Changed Recently in Document Processing?</h3>What's new is the integration of various tools into a single platform solution, which is completely changing how we work. New data sources improve business outcomes and open the road for human-driven innovation.This is a novel method of gathering and extracting data. All of the major technology companies are developing sophisticated tools, but the difficulty is that they aren't all available on one platform.Intelligent Document Processing platforms are advanced software machines that classify data from any text-based source and feed it into the data supply chain.<h3 id="what-makes-an-intelligent-document-processing-platform-so-special">What Makes an Intelligent Document Processing Platform So Special?</h3>Every step required to convert paper or digital documents into appropriately labelled data is included in intelligent document processing technologies. IDP platforms must meet the following criteria:They must be sector agnostic.Accommodate both structured and unstructured data.Integrate with cloud and on-premises content management systemsScale to process billions of extractions every dayCreate a graphical user interface for training and categorization.<h3 id="each-stage-of-document-data-integration-and-how-intelligent-document-processing-platforms-handle-it">Each Stage of Document Data Integration and How Intelligent Document Processing Platforms Handle It </h3>Document capture ? To digitize tangible material such as paper or microforms, the platform integrates with scanning hardware. Because not all documents are digital, a solution to speed up historically sluggish scanning operations is necessary.Data is ingested from digitally born content such as text files, PDFs, and office productivity documents via built-in integrations.Image processing - Computer vision algorithms provide image processing, which prepares a document for effective OCR and preservation. The IDP platform will produce two versions of digitized documents: one for machine-reading and one for on-screen viewing in a content management system.OCR (Optical Character Recognition) - Accurate OCR is required for machines to read text on documents. The utilization of several OCR engines is one of IDP's most important features. By synthesizing the data from numerous engines until near-perfect accuracy is attained, a "layered" method eliminates the need for better OCR.NLP- Find paragraphs, sentences, or other language pieces in your papers that express specific meaning using Natural Language Processing (NLP). NLP uses techniques including sentiment analysis, part-of-speech tagging, named entity tagging, and feature-based tagging to speed up data discovery. Classification - The majority of business documents are collections of pages containing various types of information. Machine learning and other intelligence-based techniques are used to train IDP classification engines to recognize documents.Automatic document recognition is a crucial step in deciphering the contents of a document. The days of manual data entry for categorization are long gone.Extraction - The artificial interpretation of information by the software is critical to successful data extraction. Because artificial intelligence (AI) is only as knowledgeable as to its training, the system must be able to find and classify all expected information within a page. This includes recognizing parts of natural language documents and extracting certain data items such as dates, names, and numbers, among other things.Data Validation ? To be trustworthy, every extracted data must be verifiable. IDP solutions are unique in that they validate data using external databases and pre-configured lexicons. Any data that doesn't match up is detected and sent to a person to be reviewed and corrected.Integration - The needs for data integration are quite varied. IDP platforms must integrate with all downstream applications since they are essential sources in the data supply chain. This comprises databases and document repositories in the cloud and on-premises. For portability, labelled data and metadata are connected to human-readable versions of the data.<h3 id="how-to-use-intelligent-document-processing-to-your-advantage">How to Use Intelligent Document Processing to Your Advantage?</h3>The development of document data literacy is the key to success with IDP platforms. Before training software to integrate data, a significant amount of work must be spent learning what data is provided and the business risks that are associated with that information.It is necessary to engage subject matter experts who use the information to do work to attain document data literacy. Their in-depth knowledge of the business value and interpretation of the data on the documents they work with guarantees that the correct data is extracted and that the appropriate action is taken with it.<h3 id="whats-the-difference-between-document-capture-and-intelligent-document-processing">What's the Difference Between Document Capture and Intelligent Document Processing?</h3>The most significant difference between IDP and standard capture is the potential of development in document processing. Over a decade ago, the main players in traditional document capture stopped inventing solutions.There are two explanations for this:1) To begin with, such technologies were developed during a time when preserving compute was a priority. Their software architecture was not designed to handle the scalability requirements of today's data-intensive applications.And, because many of these platforms have evolved through acquisition, a platform-wide software re-build to match IDP's needs would be prohibitively costly.2) The second reason is that traditional document capture firms have a huge customer base. They're successful as is, and they don't want to disturb their customers' present operations by requiring an upgrade. Instead of focusing on capture innovation, they have shifted their focus to other technologies such as robotic process automation or rebranding to look to have IDP capabilities. <h3 id="top-intelligent-document-processing-vendors">Top Intelligent Document Processing Vendors</h3><ul><li><a href="https://www.ademero.com/">Ademero</a></li><li><a href="https://docparser.com/">Docparser</a></li><li><a href="http://cloud.google.com/document-ai">Google DocAI</a></li><li><a href="http://cloud.google.com/solutions/lending-doc-ai">Google Lending DocAI</a></li><li><a href="http://cloud.google.com/solutions/procurement-doc-ai">Google Procurement DocAI</a></li><li><a href="https://groundspeed.com/">Groundspeed</a></li><li><a href="https://handl.ai/">Handl</a></li><li><a href="https://www.ibm.com/products/data-capture-and-imaging">IBM Datacap</a></li><li><a href="https://indico.io/">Indico</a></li><li><a href="https://nanonets.com/">Nanonets</a></li><li><a href="https://www.ocrolus.com/">Ocrolus</a></li><li><a href="https://vidado.ai/">Vidado</a></li><li><a href="https://xtracta.com/">Xtracta</a> </li></ul><h3 id="categories-of-idp-vendors">Categories of IDP Vendors</h3>To make it easier for you to explore the landscape, we've divided the vendors into categories:<blockquote>Vendors of innovative IDPs Vendors of legacy IDPs</blockquote><blockquote>IDP merchants who specialize in a specific niche</blockquote><blockquote>Systems integrators who provide IDP services</blockquote><blockquote>Providers of technology with IDP components</blockquote>Vendors in each category have produced solutions that are distinct from one another because they approach the IDP dilemma through different lenses. <h3 id="suppliers-of-idp-technology">Suppliers of IDP Technology</h3>General-purpose technology components like OCR and computer vision are available on the major technology platforms. Because these components aren't whole IDP solutions, we've merely included them in this piece because some businesses prefer to develop capabilities internally using existing technological components.<ul><li>Textract by Amazon</li><li>Google Cloud Vision is a service provided by Google.</li><li>Computer Vision in Microsoft Azure </li></ul>The Engine for Transformation is Intelligent Document Processing. Data plays a key role in transformation in all organizations. They obtain important insight needed to disrupt their market by producing something new by gaining new sources of data or finding new techniques of analysis.The most crucial aspect of "becoming digital" is data. It has been predicted that data will become the new trend, and that moment has come. Because digital transformation produces value-added services, products, operational strategies, and capabilities, data is the single most crucial component for innovative success. <h3 id="final-thoughts">Final Thoughts</h3>Data is a key enabler of digitalization, and companies that invest in intelligent document processing will remain on the cutting edge of innovation and growth. IDP supports the modern industry by integrating a steady stream of useful data into software applications. As we re-imagine how we work, new workflows become revolutionary business partners.

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