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."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."
"Has algorithms that can detect a document template even if the image has a lot of distortions."
"We have seen pretty good accuracy."
"What I liked more about HyperScience was the quality of the OCR it is a lot better compared to Google."
"I like that compared to other tools, HyperScience works best with handwritten documents."
"Valuable features include tools like IQ Bot and the ability to extract handwritten documents with 93-95 per cent accuracy."
"For me, the most valuable aspects of UiPath Document Understanding are its time efficiency and minimal human intervention."
"It's great for document understanding for invoices and installments."
"UiPath Document Understanding's image file extraction feature is the best in any OCR solution."
"The machine learning (ML) extractor is valuable. It helps in extracting information from even unstructured documents. It can sometimes also extract information from a written document. Without much manual intervention, it is able to process the documents. This is a unique feature of UiPath Document Understanding."
"UiPath Document Understanding offers multiple types of extractors, which we can use to extract information from documents in a variety of ways."
"UiPath enables us to automate manual tasks and duplicate them easily. The processes are highly accurate."
"Has a very good machine learning feature."
"Machine learning is the most valuable feature of UiPath Document Understanding."
"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."
"Extracting tables from certain documents could be improved."
"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."
"HyperScience could improve the unstructured data extraction feature."
"They could work on the price and make it a bit more reasonable."
"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."
"The solution lacks support for a greater range of languages."
"Existing models have room for improvement."
"I would like to see more integration of artificial intelligence. That's being implemented, but it would be a massive improvement to the solution's document processing. If UiPath achieves intelligent document processing, it will be far better than anything on the market. There are currently some limitations with the fields that could be addressed using a GPT engine. With an integrated AI model, you wouldn't need to create your taxonomy. You would only need to provide some prompts, such as "What is the property name?" It will store that as a variable."
"There is room for improvement in handwriting processes."
"Sometimes, when the number of items is very large, the solution doesn't properly identify them."
"UiPath could improve its analytics and interface."
"The licensing model poses a significant challenge due to the fee charged for posting a model, which impedes the development of productivity-enhancing models."
"Sometimes we have challenges when we need to read something like a barcode, so we must use the Cisco algorithm to solve the issue, or I have to ask developers for help specifically to capture this kind of information. There are other processes, such as refunds, that we still must do manually because there is no way to use automation to solve this issue."
"This is an expensive solution."
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HyperScience is ranked 6th in Intelligent Document Processing (IDP) with 7 reviews while UiPath Document Understanding is ranked 2nd 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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