WIRED held a great virtual event called RE: WIRED where esteemed machine learning thought leader Kai-Fu-Lee spoke about the future of AI and its potential. The discussion covered a lot of aspects including privacy, transparency, and bias where ML is used. One topic covered was the issue of “explainability” of AI, where Mr. Lee says […]
In order to refresh your memory… here are Part 1 & Part 2. In this last part 3 covering the issue of training samples, we come to the most complex part of the process of curating training sets – High Variance document types. Looking at the Explanation of Payment (EOP) document within insurance payments as […]
I routinely like to juxtapose IDP software with other enterprise software mostly because the differences, while routinely neglected, are vast, and we’re not just talking about applications or features and functionality. When it comes to most enterprise software, emphasis is on user or process efficiency or introducing new capabilities to the business all of which […]
What is the most important feature of an Intelligent Document Processing (IDP) product? Hint: You already know but you don’t spend enough time on it. Before I get to the point, let’s discuss how IDP software is different from most other enterprise software. Features & Functionality – The Hopeless Scorecard of Enterprise Software We’ve all […]
Everyone talks about AI (and more appropriately machine learning) as being the silver bullet to the challenge of achieving highly efficient business processes. And on the surface, the excitement and perspectives appear appropriate. After all, machine learning has the ability to see things in data that humans might never notice and automatically perform tasks with […]
Within practically any industry, key processes hinge upon access to information and data stored within documents and it is no less in healthcare. Even with significant advancements with EHR/EMR and interoperability, use of documents continues to flourish due to a number of factors including that documents are easy to use, and changing from documents to […]
Here are some guideposts that are useful in evaluating the authenticity of an AI capture product – whether it’s really cognitive capture.
Key factors driving IDP adoption involve data science and specifically the confidence score that is arguably the most important factor involved with any decision to adopt IDP.
Acquiring automation solutions often means conducting a Proof of Concept or evaluation because technology solutions are often too complex to assess simply by comparing a list of features. Find out how to conduct a successful PoC here.
Now that Software-defined Intelligent Document Processing (IDP) is here, is gathering input data really that big of a problem? Find out here.
Here’s a dirty, little secret about IDP software vendor claims and how to truly automate document-oriented tasks.
RPA adopters eager to expand RPA to automate more complex tasks requiring humans to open and read documents are looking to intelligent document processing.
