How AI and machine learning technology applications locate and extract relevant information from hard-to-understand, complex images.

How to maximize accuracy in capture and recognition by best leveraging your truth data.

OCR: Does Your Software Lack Confidence–explores variations in confidence scores and what this means for high quality results in invoice, receipt and check processing.

A/P Processing Automation: Think outside the manual by exploring new approaches to processing invoices, receipts, checks.

How to address the hidden challenges of faxed and black/white printed structured claims forms with excessive “noise” and scaling problems.

Is Check Payee Line Verification still necessary? It turns out it is for fraud prevention and regulatory compliance. Find out more here.

Where document capture and machine learning intersect, find out how machines continue to learn.

Let’s demystify machine learning–what we’re talking about when we talk about LEARNING. Within document capture arena, which includes both classification and data extraction from documents, automated or machine learning and training have advanced capture and recognition beyond OCR.

What’s important—accuracy or efficiency in document classification and data extraction? How to gain the benefits of both accuracy and efficiency in your automated business processes.

Advanced Capture: find out how to improve context for successful and accurate document recognition. We sat down with Tatyana Vazulina, the Product Manager at Parascript, to discover the keys to applying context for successful and accurate document recognition.

New market needs and competition play an integral role in a BPO’s decision to adopt new technologies. Adopting and implementing new technology leads the service provider down a path of risk, and this has to change.

Pattern recognition applied to data “trapped” in customer claims, invoices, and receipts enables predictive analytics and provides new revenue opportunities to BPOs.

From Vendor to Trusted Partner, the Parascript Accelerator Program for BPOs removes the significant risk associated with the adoption of new technology and ensures improved profit and the ability to address new markets

Auto-Classification Revisited: what is the error rate of your document classification system? Successful auto-classification is efficient and reduces costs. A key component to this success is achieving low error rates.

Using approaches like regular expressions and keywords on OCR text achieves poor results with double-digit error rates. Achieving excellent data extraction results requires machine learning and other advanced technologies