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Approximately 350,000 specimen labels make up Yale University’s Herbarium collection. The labels are highly unstructured and contain cursive handwriting, some of which dates back 160 years. Yale wanted to make the information computer-accessible while creating significant efficiencies. By capturing data from specimen labels, A2iA DocumentReader enables easy and efficient electronic search and view of the archives. It unlocks valuable cursive handwritten information, previously unavailable in electronic form, for scientists, researchers and educators worldwide.

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A2iA is an award-winning developer of handwriting recognition, text extraction and document classification software. With simple, easy to use and intuitive toolkits, A2iA delivers add-on features to speed automation, simplify customer engagement and quickly capture all types of data from documents – whether captured by a desktop scanner or mobile device.