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Hyland Brainware vs UiPath Document Understanding comparison

 

Comparison Buyer's Guide

Executive Summary

Review summaries and opinions

We asked business professionals to review the solutions they use. Here are some excerpts of what they said:
 

Scalability Issues

No sentiment score available
Sentiment score
8.5
UiPath Document Understanding is scalable for enterprises, but challenges exist with training, language variations, and integration of AI.
 

Valuable Features

No sentiment score available
Sentiment score
8.7
UiPath Document Understanding streamlines document processing with ML, OCR, integration, and customization, enhancing accuracy while minimizing manual effort.
The integration with UiPath Studio is smooth, making it easy to create and use machine learning models.
This solution has played a significant role in drastically reducing human errors by ensuring that 95% to 98% of tasks are done through the system.
 

Room For Improvement

No sentiment score available
Sentiment score
5.0
UiPath Document Understanding needs improvements in pricing, accuracy, integration, and support for diverse document formats and languages.
Instabase is faster than UiPath.
They can include some features in utilizing the product of assessment understanding, or more specifically, a better efficient handling of the ML skill.
 

Stability Issues

No sentiment score available
Sentiment score
7.5
UiPath Document Understanding is considered stable, rated 6-10/10, with infrequent crashes and cloud operations enhancing reliability.
 

Customer Service

No sentiment score available
Sentiment score
8.7
UiPath Document Understanding's support is generally reliable and helpful, though users sometimes report delays and communication issues.
They often ask us to go through the documentation first instead of directly explaining or addressing the root cause of issues.
Sometimes they come to our office and prepare some POCs with UiPath tools.
 

Setup Cost

No sentiment score available
No sentiment score available
UiPath Document Understanding is costly, especially for small businesses, despite flexible plans and potential ROI justifying expenses.
 

Categories and Ranking

Hyland Brainware
Ranking in Intelligent Document Processing (IDP)
15th
Average Rating
0.0
Number of Reviews
0
Ranking in other categories
No ranking in other categories
UiPath Document Understanding
Ranking in Intelligent Document Processing (IDP)
2nd
Average Rating
8.2
Reviews Sentiment
7.5
Number of Reviews
50
Ranking in other categories
No ranking in other categories
 

Mindshare comparison

As of November 2024, in the Intelligent Document Processing (IDP) category, the mindshare of Hyland Brainware is 2.7%, up from 2.7% compared to the previous year. The mindshare of UiPath Document Understanding is 16.0%, up from 8.2% compared to the previous year. It is calculated based on PeerSpot user engagement data.
Intelligent Document Processing (IDP)
 

Featured Reviews

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José Arthur Brasileiro - PeerSpot reviewer
Is easy to configure, user-friendly, and produces accurate results
The data we extract using Document Understanding relates to vehicle accidents. The insurance company uses this data to charge third parties involved and recover most of their money with minimal human intervention. We are extracting information from 50 insurance documents to prove the concept of showing coverage for those involved in the accident. The information from the insurance company is in PDF format and is structured so that we can easily extract information from it. The other public policy documents vary in quality depending on the state and district in Brazil. We have 27 states, and these documents are unstructured, making it difficult to extract data from them. Sometimes they are in image format, and other times they are in PDF format. The 50 structured PDF documents from the insurance company are all 100 percent automated using UiPath Document Understanding. We are impressed with the machine learning and AI capabilities of Document Understanding. We can use APIs to identify whenever a vehicle accident is reported, which helps our business. Using the AI we can access vehicle accident reports and train the machine learning to understand the majority of the documents we extract information from to help improve our business processes. We use the UiPath platform orchestrator with an API to integrate with OpenAI. UiPath Document Understanding has helped our organization demonstrate to potential customers how the solution, together with AI and machine learning, can benefit their businesses. Before Document Understanding our process took 15 minutes per document and now it takes under one minute. Document Understanding has helped free up our staff's time to work on other projects.
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816,406 professionals have used our research since 2012.
 

Top Industries

By visitors reading reviews
University
16%
Healthcare Company
13%
Manufacturing Company
13%
Financial Services Firm
7%
Computer Software Company
16%
Financial Services Firm
15%
Real Estate/Law Firm
9%
Healthcare Company
7%
 

Company Size

By reviewers
Large Enterprise
Midsize Enterprise
Small Business
No data available
 

Questions from the Community

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What do you like most about UiPath Document Understanding?
The solution allows us to continue with vendors whose information comes in correctly and to stop the automation for vendors with many items that are not clearly defined.
What is your experience regarding pricing and costs for UiPath Document Understanding?
I find the pricing to be fair. It's neither expensive nor cheap, but rather affordable, which makes the platform appealing to users.
What needs improvement with UiPath Document Understanding?
UiPath Document Understanding's training can be improved to focus more on how to handle the robots. Extending the trial period for UiPath Document Understanding from three to six months would allow...
 

Learn More

 

Overview

Find out what your peers are saying about ABBYY, UiPath, Automation Anywhere and others in Intelligent Document Processing (IDP). Updated: November 2024.
816,406 professionals have used our research since 2012.