Transform Multi-Channel Data into Information with Capture Technology

Executive Summary

Documents and semi-structured information are crucial to digital business; they serve as input for processes and are a vital source of insight. Many times, however, the data remains locked in paper documents or in “dumb” static images. It is often seen simply as historical data for records keeping or other archival purposes. Consider that some of this data, such as patient records or insurance claims, must be unharnessed to provide the complete picture and full understanding for decision making. Increasingly, content is created, accessed and submitted into a process from mobile devices rather than from PCs or scanners. In response to changing business dynamics, capture software has evolved to enable data from any input channel to be transformed into actionable information. With Capture 2.0 software and services, multi-source data (from paper to rich media) can be classified, validated, understood and, where appropriate, extracted for automatic entry into a business process or application.

The Capture Software market has grown at double-digit rates since 2016, due to an improved worldwide economy, greater demand for capture technology to support digital transformation and to feed analytic systems, and growth in Cloud Capture Services. Robotic Process Automation (RPA) is also having a positive impact on the demand for Capture Software in answering the need for cognitive automation. As Capture Software becomes more deeply integrated into business processes, however, it is increasingly being optimized and packaged to address the needs of specific vertical industries as well as horizontal applications.


In a data-driven economy, companies face increased demand for real-time insights into all incoming data. Many times, however, that data remains locked in unstructured and semi-structured content and must be unharnessed to provide the complete picture and full insights for decision making. The ability to have automated capture, content understanding, identification, and relevant data extraction for use in today’s business
systems and applications is critical.

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