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.
Parascript is working with more and more service providers that need to perform data extraction, which must be as accurate as possible to ensure business operations are successful and dependable. This article delves into how service providers best ensure accurate data extraction and ground truth data.
Best practices in document management—when approaching a document management challenge that necessitates data extraction—require fully understanding the types of documents involved. The “nature” of the document is fundamental in determining the most appropriate technologies and techniques to use. For example, OCR cannot provide a comprehensive solution in many cases. Instead, OCR acts as the underlying, supporting technology that aids with producing a final result.
Here we cover how to address the problems posed by a legacy system that has inadequate metadata in terms of both detail as well as coverage. Existing document types don’t have the metadata needed to support efficient governance and use, and new document types need to be created. Unless an organization is familiar with the […]
