The AOTM IDP pre-processing stage involves machine learning algorithms and Optical Character Recognition (OCR), scanning documents and detecting poor-quality images. Once detected, images of poor quality are automatically enhanced or rejected if the image quality cannot be enhanced. The pre-processing stage is crucial as it ensures high-quality extraction with accurate data per your SLAs and IDP requirements.
The initial phase of Intelligent Document Processing begins with classifying the type of document being processed. With the help of adaptive OCR, Computer Vision (CV), Natural Language Processing (NLP) and machine learning technology, you can classify documents such as invoices, purchase orders,billsl of lading, Performa invoices, bank statements, credit notes, and insurance forms.
The next step is to extract valuable information from the documents. The adaptive OCR and Natural Language Processing (NLP) recognise characters and symbols as it scans the documents. With HITL, >99% accuracy can be achieved.
IDP validates extracted data using business rules, document comparisons, and other sources. To ensure the data is accurate, it is crucial to verify it. Data that passes validation is delivered for processing, while data that doesn’t pass validation can be fixed.
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