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. Many consider it to be historical data for records keeping or other archival purposes. Consider that companies must unharness some of this data in order to provide the full picture and understanding for decision making. Such information often includes patient records or insurance claims.

Increasingly, we create, access, and submit content 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. This is 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. It has done this by answering the need for cognitive automation. As Capture Software becomes more deeply integrated into business processes, however, it becomes increasingly optimized and packaged to address to needs of specific vertical industries and 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. Additionally, companies must unharness it 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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