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Handwritten Text Recognition (HTR):
Status quo, challenges and solutions

Leverage AI to cope with handwriting

Capturing and processing handwritten documents and forms are commonplace problems for many companies in various industries, making continuous business processes an impossibility.

Neither traditional nor machine learning-based optical character recognition (OCR) technologies are up to this challenge. Only with the help of different deep learning architectures and methods can handwritten documents (Handwritten Text Recognition, HTR) be captured with an accuracy that can also deliver high-quality results and enable more efficient straight-through processes.

Handwritten Text Recognition

This whitepaper highlights the full range of options for implementing, scaling and leveraging Intelligent Document Processing.

Download your exclusive copy of the HTR whitepaper today and learn how people can unite with software to create an even more prosperous future.

Why Parashift?

According to Microsoft, more than 500 billion documents are generated worldwide every year by Office applications alone. That’s a lot of information that can still be read and interpreted by employees but can hardly be used for automatic processing and process control.

The result is media disruptions that induce unnecessary inefficiencies in processes. With Parashift, we offer you a solution for integrating documents cost-effectively into IT applications and workflows.

With the Parashift Platform, companies can easily read out their documents – no matter how many or what type of document they are.

The data obtained can then be used to make the company’s own processes more efficient or to support completely new digital business models.