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5 Ways Hyperscience Unravels the Human in Every Document

Enterprises today use many well known legacy technologies for data extraction within their back offices. The problem with many of these tools is that they cannot reliably identify, read and transcribe diverse layouts, text inputs and real-world degradations. Optical Character Recognition [OCR] tech, as an example, requires pristine conditions to operate accurately; when it’s faced with messy handwriting, crossed out lines or text outside a bounding box, it fails.

 

At Hyperscience, we understand structured documents in perfect, machine typed condition are not the reality of what businesses receive. This is why we approach document processing and data extraction differently. With Hyperscience, forms and documents fed into our Intelligent Document Processing [IDP] platform don’t need to be in perfect order for data extraction. By basing our document processing platform on Machine Learning, our solution can look beyond these mishaps and keep improving over time; decreasing the need for human involvement and manual oversight. 

 

Our latest infographic dives into common document flaws that don’t phase our Intelligent Document Processing [IDP] solution. Coffee stains, fax marks, or other degradations? No problem, our solution is built for real-world reading and data extraction.

 

When we talk about automation and digitizing data extraction within back offices, we often look at how quickly and efficiently workflows operate. Businesses know the errors and costs that occur when the bulk of document processing is dependent on manual data entry or outdated capture software, but miss the errors that happen before a document even enters the back office. Choosing an Intelligent Document Processing [IDP] solution can resolve these pain points while increasing efficiency and automation.

key learnings

[1]

5 common document imperfections our intelligent machine learning system can still extract data from

[2]

How legacy solutions like OCR can’t keep up with flawed documents

[3]

The impact of our solution’s ability to understand intent