SoftWorks AI Technologies, a leading provider of OCR, PDF optimization, and business process automation solutions, has optimized processing for image documents as well as native PDF files with electronically generated components.
Auto-validation is a touchless process that is faster and more accurate than manual validation. Documents qualify for auto-validation when they fit an organization’s unique, customizable business rules, or when they hold a high text confidence factor (this threshold is configurable and typically sits near 90%).
With the Electronic PDF Parsing Module for SoftWorks AI’s Trapeze for Forms Processing, organizations can expect to achieve a 90-100% text confidence factor on average, allowing for greater auto-validation rates and a faster, more efficient workflow. For example, if half of an organization’s documents are native PDF files, this module can increase total auto-validation rates by 30-50%.
The Electronic PDF Parsing Module enables SoftWorks AI’s Trapeze for Forms Processing solution to intelligently distinguish between scanned PDFs and electronic PDFs, also known as native PDF files. Whenever an electronic PDF is detected, Trapeze will bypass the resource-intensive and time-consuming OCR process, a powerful function that typically improves system performance by as much as 80%. Consequently, this function also allows Trapeze to dedicate newly freed up resources toward processing more image documents in a shorter period of time. In this way, extracting PDF data electronically improves accuracy and throughput, making the overall document-based workflow more efficient.
Greatly improve system performance by bypassing the resource-intensive OCR phase for existing text layers.
Bypassing OCR for existing text improves text confidence factors for greater accuracy and more automation.
Free up processing resources previously spent on digitally born files to recognize, classify, and extract data from batches of image documents more quickly.