Many companies are overwhelmed by the abundant volume of documents they have to process, organize, and classify to serve their customers better. Examples of such can be loan applications, tax filing, and billing. Such documents are more commonly received in image formats and are mostly multi-paged and in low-quality format. To be more competitive and cost-efficient, and to stay secure and compliant at the same time, these companies must evolve their document processing capabilities to reduce processing times and improve classification accuracy in an automated and scalable way. These companies face the following challenges in processing documents:

Performing moderation on the documents to detect inappropriate, unwanted, or offensive content
Manual document classification, which is adopted by smaller companies, is time-consuming, error-prone, and expensive
OCR techniques with rules-based systems aren’t intelligent enough and can’t adopt to changes in document format
Companies that adopt machine learning (ML)

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