Optical character recognition (OCR) is a process by which specialized software is used to convert scanned images of text to electronic text so that digitized data can be searched, indexed and retrieved. OCR engines are developed and optimized for multiple real world applications such as extracting data from business documents, checks, passports, invoices, bank statements, insurance documents, license plates and more. Each of these applications require processing data sets that consist of hundreds of thousands scanned documents or images in order to train and optimize the algorithms. Processing the training data set is typically done by humans in order to provide accurate data that can be used by the engine to learn and apply, making it "smarter" over time.
Processing these large data sets can be costly, and leveraging a crowdsourcing model to reduce the cost often leads to low quality outputs that will not be sufficient to improve and perfect your engine.
Our unique blend of technology and human intelligence, which is powered by a managed workforce provides you with a scalable and affordable solution to process these large data sets efficiently and accurately so you can improve your OCR processes faster and scale smarter.