Demand among enterprises to enable end-to-end process automation with integrated RPA and IDP.Increased adoption of complementary technology solutions, such as RPA.Rising need to process large volumes of semi-structured and unstructured documents with greater accuracy and speed.
#PHROZER MUSIC TAG DRIVERS#
Everest Group cites the key drivers behind the growth of IDP: 80-90% of enterprise data and documents are unstructured and require the integration of different technologies to turn it into a machine-readable format. Intelligent Document Processing leverages automation tools such as RPA to collect, extract data, and generate documents. AI technologies such as natural language processing (NLP), Computer Vision, deep learning and machine learning (ML) are used to classify, categorize, and extract relevant information, and validate the extracted data.
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Business data is at the heart of digital transformation unfortunately, 80% of all business data is embedded in unstructured formats like business documents, emails, images and PDF documents. Intelligent Document Processing (IDP) solutions transform unstructured and semi-structured information into usable structured data. While OCR is notorious for transcription errors, intelligent document processing, which is AI-driven, starts at higher accuracy, and will improves over time.
These systems are grounded in computer vision and natural language processing techniques that are used to grab visual information from the document and ensure that it’s parsed correctly. Today, document processing typically relies on multiple, synergistic machine learning techniques to read a document, extract its relevant fields, and perform intelligent processing on top of that. The discipline has progressed due to its early venture into OCR-based approaches. IgnitionOne currently scores over 300 million users monthly in 75 countries and powers more than $30 billion in revenue each year for leading brands, including General Motors, CenturyLink, Bridgestone, La Quinta and Fiat, as well as advertising agencies such as 360i, GroupM and iProspect.Document processing with one of the first deep learning models-the convolutional neural network (CNN) -was originally developed in 1990s for banks to automatically process checks and for post offices to automate the processing of handwritten mailing addresses. At the core of the DMS is the proprietary User Engagement Score Algorithm which determines the value of a user in order to automate the delivery of the right message, at the right time, at the right cost, to a marketer's users, on and off their website. IgnitionOne's integrated Digital Marketing SuiteSM (DMS) empowers marketers to buy, manage and optimize digital media across Search, Display, Social and Mobile, understand client users through Data Management and Cross Channel Attribution, while helping to optimize conversions on a marketer's website through Marketing Automation. IgnitionOne(R) is the global leader in cloud-based digital marketing technology providing a world-class proprietary platform and expert services to improve digital marketing performance.
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