Enterprise OCR servers let you perform Optical Character Recognition on thousands of documents at a time, scaling to meet the demands of the largest document conversions.

Traditional Desktop applications require a person to load the scanned document, run the process and save the output files. This makes sense when you are converting individual documents, but large organizations with thousands or millions of documents need something much more automated and scalable.

OCR Server processing workflow

Typical Enterprise Applications

As the cost of OCR software and hardware goes down each year and the quality goes up, full-text search is included in more and more records management applications. Typical applications include:

  • Data mining
  • Litigation support
  • Full-text searching
  • Document management

Features of Enterprise OCR Servers

  • OCR is performed in the background without a user interface
  • Files are imported automatically from hotfolders
  • Ability to use multiple CPUs and servers for processing
  • Management tools for remote administration
  • Web service & API integration to submit OCR jobs

What is the Best OCR Server?

The ABBYY FineReader Server offers the best combination of features, performance and pricing. It has flexible licensing, including an unlimited CPU-based license that does not limit the number of pages processed.

Foxit PDF Compressor has the lowest entry level pricing, OmniPage OCR and unique PDF compression technology that can dramatically reduce the size of searchable PDF documents, leading to faster viewing and lowered cloud storage and bandwidth costs.

The SimpleIndex Server offers affordable unattended OCR services coupled with advanced and indexing capabilities that organizes documents automatically or saves metadata to Excel or a SQL database. It doesn’t have the scalability, API interfaces or compression technology that other OCR servers have, but you can bundle the Standard Server version with them to add indexing, and automatic organization to your solution.

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