Are checklists useful in document automation evaluations? Here’s a checklist approach & one that requires a new approach to evaluate technology solutions.
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Are checklists useful in document automation evaluations? Here’s a checklist approach & one that requires a new approach to evaluate technology solutions.
Don’t just OCR documents. Interpret them. Find out how document interpretation is central to cognitive document automation for the digital workforce.
When using advanced capture, are templates such a bad thing? This article explores the use of the “template” and when it makes sense to go “template-less.”
What is a document & its future? A document is a container for data—not stored in rows and columns—that is paper-based or electronic. Discover more here.
RPA allows organizations to “rediscover” advanced capture with solutions that are simple to use with advanced capabilities. Find out more here.
Artificial intelligence (AI) at your organization: if AI won’t improve your organization should you deploy it? Find out if, when and how here.
A joint investigation by Fortune Magazine and Kaiser Health News offers a very useful case study of sorts for the negative ramifications of digital transformation projects that are not well-defined or coordinated. The results of this investigation were published in a recent long-form article by Fortune called, “Death by a Thousand Clicks.” You’ll want to […]
Signature Verification: Will Automation Improve Citizen Engagement? It’s a very real possibility. Find out how and why here.
OCR software often fails to meet business expectations due to some common misconceptions. Some alternatives are explored here.
Google, Amazon, Microsoft & Advanced Capture: are these comparing apples to apples? Article explores differences between OCR software and advanced capture.
Document automation applied machine learning (ML) platforms are running up against generic ML platforms: how do they compare? Trade-offs considered here.
Addressing machine learning and its voracious appetite for data requires feeding it volumes of quality data–a primer on types of ML and the data they need.