The Future of Data Extraction: A Comprehensive Guide to Intelligent Document Processing Technologies

 


Quadrant Knowledge Solutions defines Intelligent Document Processing (IDP) as a method for automatically extracting valuable information from documents received by an organization in various formats, including structured, semi-structured, and unstructured documents. IDP leverages multiple technologies such as Artificial Intelligence (AI), Machine Learning (ML), Optical Character Recognition (OCR), Computer Vision, Robotic Process Automation (RPA), Natural Language Technology (NLT), and Intelligent Character Recognition (ICR).

These technologies work together to extract, interpret, and classify relevant data from word files, emails, PDFs, scanned documents, and other formats, facilitating analysis and workflow automation. Utilizing a template-free approach, IDP can extract data from unstructured documents with its no-code platform, enabling human-in-the-loop (HITL) capabilities to identify hidden information and correct extracted data in real-time.

Additionally, the platform can identify sensitive data fields, such as those containing personally identifiable information (PII) and apply data masking to redact or anonymize them. This supports various use cases, including invoice automation, lease and contract processing, customer onboarding, account opening and closing, financial reporting, and insights and analysis.

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Key questions this study will answer include:

·       Is the Intelligent Document Processing (IDP) market growing? What is the short-term and long-term growth potential of the IDP market?

·       What are the key market accelerators and restraints impacting the global IDP market?

·       What are the major end-user industries for IDP solutions? Which industries offer maximum growth opportunities during the forecast period?

·       Which global region offers the most significant growth opportunities in the IDP market?

·       Which customer segments have the highest adoption of IDP solutions?

·       What are the various deployment options for IDP solutions?

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Strategic Market Direction  

The rise of cloud storage in automated document processing allows for the secure storage and access of data from processed documents from anywhere, making it ideal for remote teams and businesses with multiple locations. Cloud providers also offer features such as automated backups and version control, which facilitate document management and collaboration. Additionally, users can seek vendors that provide blockchain technology for enhanced security, offering an immutable and decentralized ledger to track the entire lifecycle of a document from creation to distribution, ensuring it is tamper-proof and secure.

 This capability helps maintain a clear audit trail of document access, preventing fraud and unauthorized access. Furthermore, the use of natural language processing (NLP) and optical character recognition (OCR) technologies allows for quick and accurate document retrieval through keyword and phrase-based search queries.

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Vendors covered in this study:

ABBYY, Alkymi, AntWorks, Appian, Automation Anywhere, Celaton, Code mantra, Datamatics, Edge Verve System, eigen Technology, Grooper (BIS), HCL Technologies, IBM, Indico Data, Infrrd, JIFFY.ai, Knowledge Lake, Kofax, Laiye, Microsoft, OpenBots, Parascript, Parashift, qBotica, Rossum, Stravie, UiPath, UST, and Work fusion.

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