Often in conversations with clients and prospective clients, we hear phrases such as “we want to get 90 percent accuracy” from our system, but what does that really mean?

For companies with high volume document processing needs that are either processing in-house or outsourcing these tasks, it’s worth examining the level of automation currently used and if AI and machine learning are even under consideration.

BPOs with services fragmentation are increasingly at risk since they have often electing to procure technology on a project-by-project (a.k.a., client-by-client) basis, but there are approaches to overcome this fragmentation.

Now is the time for restrictive endorsement in fraud prevention, which means financial institutions will need to implement technology to detect the presence of the restrictive endorsement in addition to the signature.

When it comes to the classification of documents, one accepted approach is using text. And yet, visual classification can offer a powerful alternative.

Getting good and reliable OCR accuracy from your system may involve more than you think.

Panorama of AP automated solutions–traditional approaches versus machine learning and how to determine what solution works best for you.

This AIIM webinar focuses on how capture leaders are running their large document processing operations, their challenges and how they address them.

How to move beyond features and attributes in document processing automation to identify the solution that best meets your enterprise’s needs.

Capture and recognition engines vary widely in ease-of-use and configuration automation is key to adopting advanced capture software–find out why here.

Artificial intelligence may outperform humans in 45 years although AI today is highly constrained and applied in its actual smarts. What happens between now and tomorrow?

Outsourcing to reduce cost is one important reason for selecting a Business Process Outsourcer, but it’s not enough as companies look to their BPOs for additional services.

All indications are artificial intelligence (AI) will transform our future in significant ways. Today, AI already automates many activities that were typically relegated to humans, but how exactly did we get here?

Explore how business-critical data waiting to be released to the workflow process could be captured and mined for relevant facts that impact decision making.

Why can’t capture and recognition software read fields that a person can read and how does it read what we find hard to read? The answer: neural nets.