We performed a comparison between HyperScience and UiPath Document Understanding based on real PeerSpot user reviews.
Find out in this report how the two Intelligent Document Processing (IDP) solutions compare in terms of features, pricing, service and support, easy of deployment, and ROI."I like that compared to other tools, HyperScience works best with handwritten documents."
"We have seen pretty good accuracy."
"It provides the best accuracy for handwritten forms, which is a struggle in the industry. You can take processes with a lot of manual work and streamline them through this tool."
"One of the most valuable features of HyperScience is the user-training module. Whenever the extraction takes place, based on the way we have trained HyperScience, it would give us some success status or a certain confidence level. If the solution has processed something that it determined was not extracted correctly it will queue those items for manual review."
"Valuable features include tools like IQ Bot and the ability to extract handwritten documents with 93-95 per cent accuracy."
"Has algorithms that can detect a document template even if the image has a lot of distortions."
"What I liked more about HyperScience was the quality of the OCR it is a lot better compared to Google."
"The quality of the input documents is crucial because sometimes healthcare providers prefer automated processing rather than human review."
"UiPath enables us to automate manual tasks and duplicate them easily. The processes are highly accurate."
"I like the clear and organized way in which UiPath has structured the labeling process, as well as the user-friendly development environment."
"The entity-level extraction is very good. The workflow is also very good."
"UiPath Document Understanding offers multiple types of extractors, which we can use to extract information from documents in a variety of ways."
"The highly visual and user-friendly interface was a standout feature."
"The best feature, in my opinion, is, we can train the document using a machine-learning classifier."
"The most valuable feature is the ability for humans to train the bot."
"The solution lacks support for a greater range of languages."
"No solution is perfect and there are several different scenarios that could be improved in HyperScience. One area is where there are multiple tables in the same form I have seen HyperScience struggle. There is some issue with supporting the extraction from multiple tables involved on the same form. If this could improve, it would be a big benefit."
"Extracting tables from certain documents could be improved."
"HyperScience has less capability while working on unstructured forms. Unstructured forms are those where there is no standard structure and the information can be anywhere on the form. They need to develop this capability."
"HyperScience could improve the unstructured data extraction feature."
"They could work on the price and make it a bit more reasonable."
"The product's usability could be better. The first pain point is that we're getting the output in a different format, and we were expecting a different timetable. The second point is that if you want better results, HyperScience says you have to configure a minimal PDF or a maximum of 400 PDFs. If you want results with 400 PDFs for what's written by these doctors, then you also configure the maximum of 400 templates for that. So, it's essentially a lack of support from HyperScience. In the next release, it would be better if failure scenarios were reduced. It would also help if they offered different formats, inputs or injections, and added different scenarios."
"I would like more flexibility in Document Understanding's validation center."
"I encountered difficulties with UiPath Document Understanding in determining the appropriate OCR to use for certain files."
"UiPath Document Understanding requires more database connectors."
"An area for improvement in UiPath Document Understanding is data extraction from scanned documents. It could be better because I've observed a ten percent failure or flaw whenever the vendor scans and converts documents into PDFs."
"Document Understanding's handwriting comprehension is improving, but it's still not as good as printed documents. Machine learning models, in general, are becoming mature, but it's still not to a point where I will give it five stars. I may give it a two or three. It is still not advanced enough to identify whatever handwritten content you give to it. It can process handwriting, but you need a human to validate it. With more training, it will become more automated. It will be better by 2025, but it is still not mature enough"
"It would be ideal if they could include more packages for more use cases."
"There is room for improvement in UiPath Document Understanding's pricing. It is expensive for small clients. Currently, there is a big gap between the basic package and the 200,000 packages. There is no package in the middle for small agencies."
"UiPath Document Understanding's ability to handle diverse document formats, including scans and signatures, needs improvement."
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HyperScience is ranked 6th in Intelligent Document Processing (IDP) with 7 reviews while UiPath Document Understanding is ranked 3rd in Intelligent Document Processing (IDP) with 45 reviews. HyperScience is rated 7.6, while UiPath Document Understanding is rated 8.2. The top reviewer of HyperScience writes "It has a lot of functionality, whatever we use, but a few things could be improved". On the other hand, the top reviewer of UiPath Document Understanding writes "Is easy to configure, user-friendly, and produces accurate results". HyperScience is most compared with ABBYY Vantage, UiPath, Instabase, Microsoft Power Automate and Automation Anywhere (AA), whereas UiPath Document Understanding is most compared with ABBYY Vantage, Instabase, Tungsten TotalAgility, Nanonets and Datamatics TruCap+. See our HyperScience vs. UiPath Document Understanding report.
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