The product is very, very nice. The tool relieves the data entry team from manipulating data. It shortens the time of extracting data by 70 to 80%.
Regional Solution Architect at a tech vendor with 10,001+ employees
Does not support the Arabic language, though it shortens the time of extracting data and reduces human errors
Pros and Cons
- "It shortens the time of extracting data by 70 to 80%."
- "The solution must localize the built-in features for supporting Arabic scripts so we do not rely on third-party tools."
What is most valuable?
What needs improvement?
UiPath should localize the built-in features for supporting Arabic scripts so we do not rely on third-party tools. It will take some investment. Sometimes, when we use third-party tools, we need to collect multiple samples of the same document in Arabic. It creates some errors in understanding.
Sometimes, we need to do multiple formats for the same document. It happens due to the nature of the Arabic language. For the same document in English, we only supply one template. The output of handwritten documents in Arabic is very poor, regardless of the solution. For computer-printed documents, we need to tune the system.
For how long have I used the solution?
I am using the solution currently.
What do I think about the stability of the solution?
The product is stable.
Buyer's Guide
UiPath IXP
September 2025

Learn what your peers think about UiPath IXP. Get advice and tips from experienced pros sharing their opinions. Updated: September 2025.
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What do I think about the scalability of the solution?
The tool is scalable.
Which solution did I use previously and why did I switch?
We were using our own intelligent business processing solution. It is more convenient to use because it's our own product, and we rely on Amazon Web Services. It provides big advantages for Arabic scripts. It is more understandable.
How was the initial setup?
The product is easy to implement to an extent. If we are familiar with the input, processing, output, and how to declare variables, it's easy. If we are new to UiPath, it would be somewhat difficult to understand. UiPath Academy and certifications are very important.
The difficulties in implementation depend on the environments, document sources, document types, and customer understanding. Sometimes, customers think the product can pass anything without configuration, which is not true in some cases. We have to be very clear with the customer about the type of documents and layout they can expect. Two working days are sufficient for configuring, extracting, and linking the process. One person is enough to deploy the solution.
What's my experience with pricing, setup cost, and licensing?
The pricing depends on the context of the project. UiPath is a pricey tool for small customers. If the customer agrees on the cloud product, we discuss the cost accordingly. In some cases, even though the customer sees value in the product, return on investment, productivity, and enhancements of their processes, they decide not to choose UiPath due to budget constraints. They choose a different vendor.
What other advice do I have?
Sometimes, the customer is small, but we could see the potential for using the tool because they might have multiple processes. The price we offer is based on the context and the size of the opportunity we get for references. Document Understanding has helped us automate processes like contract management, reconciliation of invoices against purchase orders, claims management, and HR processes.
We process 100,000 to 500,000 documents in a year. We also had a project for Dubai Customs to reconcile the customs clearance, which involved 500,000 to 1,000,000 documents. These documents contain tables, bar codes, dates, and checkboxes. Tables might span over multiple pages, and we must capture it completely. It becomes challenging sometimes. If there is an invoice of three pages, everything must be captured, but sometimes the values are inaccurate.
Around 70% of our organization’s documents are completely processed automatically. We haven't used the product for signatures. Customers often see from a productivity point of view. If their employees process ten documents an hour, and the tool processes 50 documents an hour, using the tool is an advantage for them.
The tool does not work for integrations. It extracts data. When we extract data successfully, we rely on other business tools for integration. Document Understanding serves as a first milestone in the process. The tool at the second milestone would pick up the extracted data and post it according to the processes or applications used.
We need human validation of Document Understanding outputs three out of ten times. It does not take more than 20 to 30 seconds per document. An employee would take ten documents per minute. RPA could handle 30 to 40 documents per minute. Document Understanding has helped us reduce human errors by 70% to 80%.
Document Understanding has helped free up staff’s time for other projects. From a development point of view, it has freed up 70% of staff's time. From an employee's point of view, it has freed up 80 to 90% of their time. We saw the value of the product after a couple of projects, especially when we implemented it and saw the value for ourselves. As a customer, vendor, or implementer, when we see the execution, we see the value.
If someone wants to take advantage of this technology, they must think multiple times about different scenarios. They must centralize the capture or the source of data. They can use any product that is easy to use and configure and link it to the processes. They must sync the templates and the configuration multiple times and link it to the automation strategy.
Overall, I rate the solution a five out of ten.
Disclosure: My company has a business relationship with this vendor other than being a customer. Partner
Account Chief Technologist at Peraton
Saves time with processes like document classification, data extraction and automation
Pros and Cons
- "The solution removes manual processes and reduces human dependency. It takes a lot of effort to go through each physical mail or email, extract the data and transfer it to Excel. However, the solution automates the process and works 24/7. The tool gives a complete package to process and understand documents. The valuable features include taxonomy modification, classification, workstation, etc. There are out-of-the-box features like ML models which you can custom build. We have saved time with UiPath Document Understanding. We have seen a 50 percent improvement in scanning processes. Compared to humans, the tool runs 24/7. The human error rate has also been reduced. Our human error rate is five percent now compared to the previous 15 percent. UiPath Document Understanding has also freed up our staff who now spend more time on critical tasks."
- "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."
What is our primary use case?
I use the tool for a couple of my client projects. My clients receive physical mail and may need to scan data to run processes like automation on it. Another use case is document classification. The solution helps with processes like classification, data extraction, and automation.
What is most valuable?
UiPath removes manual processes and reduces human dependency. It takes a lot of effort to go through each physical mail or email, extract the data and transfer it to Excel. However, the solution automates the process and works 24/7.
It gives a complete package to process and understand documents. The valuable features include taxonomy modification, classification, workstation, etc. There are out-of-the-box features like ML models which you can custom build.
We have saved time with UiPath Document Understanding. We have seen a 50 percent improvement in scanning processes. Compared to humans, the tool runs 24/7. The human error rate has also been reduced. Our human error rate is five percent now compared to the previous 15 percent.
UiPath Document Understanding has also freed up our staff who now spend more time on critical tasks.
What needs improvement?
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.
For how long have I used the solution?
I have been working with the solution for more than five years. I started to work on the product when it was still under development.
What do I think about the stability of the solution?
I have not encountered any performance issues.
What do I think about the scalability of the solution?
The exact number of documents processed per client varies. However, it ranges between 1000-3000 per week. The documents processed are very less. We process 10-15 documents daily.
How are customer service and support?
UiPath Document Understanding's support is always ready and helpful.
How would you rate customer service and support?
Positive
How was the initial setup?
UiPath Document Understanding was easy to implement and put into production. The timeline can change when you create your ML model.
What was our ROI?
We have seen ROI with UiPath Document Understanding.
What other advice do I have?
The document format is mostly PDF and can be structured or semi-structured documents. We have not dealt with handwritten documents. Our real-time use case is for structured documents like emails and invoices. Most of the client documents go through without any errors. However, there is a five percent failure rate that needs to be considered since the document may contain unexpected data. 90 percent of documents go through it.
The solution handles signature-based documents. We are still working on that prototype. We faced issues with seals. It differs from department to department and state to state.
The tool's AL and ML features work fine for us. We leverage these features for driving licenses. AL and ML keep a check on document generation. UiPath Document Understanding has come up with an API-based document understanding model which we will leverage soon.
We implement human validation when we use anything new so that everything works as expected.
I would rate UiPath Document Understanding an eight out of ten.
Disclosure: My company does not have a business relationship with this vendor other than being a customer.
Buyer's Guide
UiPath IXP
September 2025

Learn what your peers think about UiPath IXP. Get advice and tips from experienced pros sharing their opinions. Updated: September 2025.
870,623 professionals have used our research since 2012.
RPA Consultant at Aubay Italia S.p.A.
Provides valuable machine learning, reduces human error, and speeds up processes
Pros and Cons
- "Machine learning is the most valuable feature of UiPath Document Understanding."
- "I encountered difficulties with UiPath Document Understanding in determining the appropriate OCR to use for certain files."
What is our primary use case?
Our primary use cases for UiPath Document Understanding are processing invoices for five different clients and importing/exporting documents to extract vital information, mainly from unstructured documents. These five clients are from various industries, including transportation, scientific research, food services, and clothing.
How has it helped my organization?
I processed 400 documents per day for one client and 20 documents per day for the second client.
The documents processed were in PDF format.
90 percent of the 400 documents processed per day for a single client were fully automated. However, only 50 percent of the 20 documents per day were automated due to their greater level of unstructured nature. As a result, the remaining 50 percent had to be sent to the action center.
AI and machine learning for Document Understanding are game changers. Machine learning was helpful in identifying the various areas of the documents from which I needed to extract different types of information, making the process quicker.
The default model didn't work for me because I needed to extract information from documents written in French. Thus, I had to create my own model using AI, which proved to be exceptionally beneficial for handling the French text and its accents.
Integrating UiPath Document Understanding with other systems and applications in our environment works well. The solution was able to retrieve the PDF document from an email, extract the details using the command, and apply those details to an application, saving a substantial amount of time.
UiPath Document Understanding serves as a safeguard in relation to cost and time savings, as it diminishes the manual workload for employees and minimizes errors. For a job that took a human eight hours to complete, the bot was able to do it in three hours.
The extent of human validation needed for Document Understanding varies for each client. For one client, no validation was necessary as the solution effectively extracted all required information from the documents. However, for another client dealing with diverse document types, errors occasionally occurred due to character placement. This was particularly evident when email addresses were positioned differently, some at the top and others at the bottom of the documents, posing challenges to the robot's detection capabilities. In such instances, a validation process was implemented. Every seven days, ten percent of the batch would be sent to the Action Center for validation.
The time saved with UiPath Document Understanding is exemplified by an organization that previously had to spend three days manually extracting information from 400 documents every month. However, with UiPath Document Understanding, this task now only takes two hours.
What is most valuable?
Machine learning is the most valuable feature of UiPath Document Understanding.
What needs improvement?
I encountered difficulties with UiPath Document Understanding in determining the appropriate OCR to use for certain files. These files required extracting both the company logo from the page and the digitized text, posing a challenge. The OCR engine faces difficulties when processing signatures and scanned documents with unclear handwritten text.
The robot faces difficulties in recognizing when there are multiple documents on a single page. This necessitates manual intervention by first splitting the document and then re-digitizing each part separately.
I would like a split feature in a future release of UiPath Document Understanding.
For how long have I used the solution?
I have been using UiPath Document Understanding for one month.
What do I think about the stability of the solution?
UiPath Document Understanding is extremely stable.
What do I think about the scalability of the solution?
UiPath Document Understanding is scalable.
How are customer service and support?
The technical support responds promptly and strives to resolve our issues quickly. However, there is room for improvement. For instance, we encountered an issue with the Action Center, and the support team was unable to determine the cause for three days. Eventually, someone from my team resolved the issue.
How would you rate customer service and support?
Neutral
How was the initial setup?
The initial setup was a bit complex.
Which other solutions did I evaluate?
I also assessed FlexiCapture, but I discovered that UiPath Document Understanding was more user-friendly. Coming from a scientific background, I found that UiPath Document Understanding offered a more logical and less complex solution.
What other advice do I have?
I would rate UiPath Document Understanding nine out of ten.
It took me one week to study UiPath Document Understanding and to present it to my organization.
I realized the benefits of UiPath Document Understanding once I completed my first project.
The quantity of personnel needed to maintain the solution relies on each project. In the most recent project I participated in, we needed a total of two individuals, one of whom was an administrator from our team.
When using UiPath Document Understanding, always ensure that the number of structures is the same each time to prevent errors.
I believe that utilizing communication mining would be more effective with the AI Center.
Which deployment model are you using for this solution?
Private Cloud
If public cloud, private cloud, or hybrid cloud, which cloud provider do you use?
Google
Disclosure: My company has a business relationship with this vendor other than being a customer. Partner
RPA Developer at a manufacturing company with 10,001+ employees
Enabled us to fully automate the majority of the PDFs we operate on
Pros and Cons
- "The taxonomy and Validation Station are among the most helpful features for us. If anything is extracted incorrectly, we can manually extract it there."
- "There is also room for improvement in long-running table extraction. If a table continues for more than 10 pages, in some cases, we have observed that it only extracts six or seven pages and skips the last pages."
What is our primary use case?
Our client has PDF invoices and we use the solution to extract the details from them. We are using it in finance and health care. We have about 16 templates that we process now. The data is in semi-structured format and we mostly process things like signatures and tables. Out of the 16 templates, about 12 are completely processed automatically.
How has it helped my organization?
It has helped us automate finance statements and invoice billings.
Another benefit is that it has mostly helped reduce human error. We have a criteria of 75 percent matching. Out of 10 PDFs we have been getting eight PDFs with at least 75 percent matches. It has also helped free up staff time.
What is most valuable?
The taxonomy and Validation Station are among the most helpful features for us. If anything is extracted incorrectly, we can manually extract it there.
And we have included the AI Center for our customers to interact with PDFs to be extracted. Based on the approval or rejection feature, our customer can determine which kinds of PDFs they can automate.
I also like the table extraction feature. UiPath is very good with structured data.
What needs improvement?
Handwriting is more complex. We have not been able to get handwritten signatures correctly extracted in different languages. Our customer is in Dubai, and the solution cannot accurately process signatures in the local language. But it is a great tool for handling structured and semi-structured formats.
Another of the disadvantages is that we cannot include another tool. For example, with ABBYY extraction, we can integrate the process with any other product. We can integrate Document Understanding using JSON templates, but it is a bit of a complex model to extract the data from the JSON.
There is also room for improvement in long-running table extraction. If a table continues for more than 10 pages, in some cases, we have observed that it only extracts six or seven pages and skips the last pages.
For how long have I used the solution?
I have been using UiPath for about 10 years.
What do I think about the stability of the solution?
Overall, the product is stable.
What do I think about the scalability of the solution?
In our case, the use of Document Understanding is restricted to a particular group of users, around six or seven people.
How are customer service and support?
The technical support from UiPath has been pretty good in the last year. It has been a very good experience.
We used Azure DevOps for the deployment and we faced some issues regarding the deployment with UiPath and Orchestrator. We had a very good response from the UiPath technical team.
There is some room for them to improve the speed of the response because we often used to get late responses. But the resolutions are good.
How would you rate customer service and support?
Positive
Which solution did I use previously and why did I switch?
We were using ABBYY, but it is more like a developer's tool with everything a developer needs for extracting fields. But we can train and retrain Document Understanding. In that way, I feel it's a better tool.
What's my experience with pricing, setup cost, and licensing?
The pricing is reasonable.
As for additional costs, the solution is based on OCR, and sometimes the OCR cap is exceeded. It's not a major cost. Per month, we will have two or three scenarios like that. With ABBYY, once the cap was reached, we had to wait until the next day to use it again.
Which other solutions did I evaluate?
We did not evaluate other solutions. Using Document Understanding was a requirement from the client's side.
What other advice do I have?
In terms of human validation for Document Understanding output, we have a limit of 75 percent correct scenarios. If it is below 75 percent, the user will be notified.
The solution doesn't require any maintenance unless the client requires more fields to be extracted. Only then are there changes that I need to make.
My advice is that if you are starting to learn about Document Understanding, you need to learn more about the taxonomy and what fields you are extracting. You need to have clarity on which position you are extracting, as it mostly depends on the position.
Which deployment model are you using for this solution?
Public Cloud
Disclosure: My company does not have a business relationship with this vendor other than being a customer.
RPA Developer at Anza Business Services LLP
As we process more data, the solution adapts using machine learning to classify information more accurately
Pros and Cons
- "The validation process is easy. The Validation Station shows you the extracted data on one side and the document on the other, so you can easily scroll down and check if the data is accurate. You just need to click a checkbox. If you don't think it is fine, you have the option to add an exception. Based on that exception, you can create multiple conditions for how to address the same issue if it happens again."
- "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."
What is our primary use case?
UiPath can handle normal, structured documents like forms and editable PDFs, but the data cannot be extracted from some unstructured documents with normal instructions. Non-standard documents are the most challenging thing for us. For example, let's say you have a hard copy of a receipt you get from a store, and you want to keep a record of it. You need to extract specific types of data and store it in Excel. Document Understanding can deal with these documents. You can configure it to scan the receipt and identify the data we're interested in.
We can provide a set of optimizations, classifications, and preconfigurations before we process the document. We created a taxonomy that we've predefined that these kinds of documents can conform to our security purposes. Using the taxonomy, Document Understanding can first classify the type of document, the arguments or variables we want to use, and the data we need to extract or store. Document Understanding can scan a written document and identify if a signature is present.
We keep a person in the loop in between because we can't 100 percent rely on the extraction. Document Understanding uses OCR which sometimes struggles with handwritten material. For example, it might mistake a six for a five. There must be a human in the loop to ensure quality. The device will send it to the validation station on your mobile phone. The bot will learn from the choices you make, and it will be more accurate the next time.
How has it helped my organization?
Document Understanding helps us to reduce human error. It can reduce the time staff spends on some tasks, but the amount of time saved depends on a few factors. We still need to validate the data because before proceeding, we sometimes collect and share sensitive data for our clients. We need a validation step in between to check before we send any data.
What is most valuable?
One benefit of Document Understanding is machine learning. As we process more data, we train Document Understanding to classify information more accurately. Document Understanding can extract and interpret information similar to the way a human can. A human can read a paragraph and distinguish between types of information, but our UiPath bots can't. Document Understanding integrates with artificial intelligence to interpret information within that.
The newer versions of Document Understanding can integrate with ChatGPT or any generative AI tools so that it can better interpret the information autonomously, and we don't need to create the taxonomy or classify the documents. We only need to give a prompt and input the document.
It will read documents similar to the way a human would. Let's use a contract as an example. You want to extract data like the buyer, seller, property address, etc. It will take the information from the document and give it to you. It can also scan for checkboxes and identify which ones are checked, but there are some limitations.
It uses a document object model to map which data is on what page of the document. For example, let's say the data you are interested in is on the third page of the document. The model knows where the data is, so it directly jumps to that particular page and extracts the information. The mapping is very perfect.
We always use attended processes because it's a good practice. The bot can do it without a human in the loop, but I would only do that if you are certain about which information you want to extract. If you're working with a handwritten document or signatures, you need a human in the loop to validate the data and help the machine learning component learn the difference between correct and incorrect information.
The time required for the validation process varies depending on the number of fields. For a small number, it only takes two or three minutes. When you have more fields, it may take a little longer to create and configure the document understanding model. You need to create the taxonomy, classifications, and model.
The validation process is easy. The Validation Station shows you the extracted data on one side and the document on the other, so you can easily scroll down and check if the data is accurate. You just need to click a checkbox. If you don't think it is fine, you have the option to add an exception. Based on that exception, you can create multiple conditions for how to address the same issue if it happens again.
Document Understanding is about 75-100 percent accurate depending on the type of document, and it increases as you train the model.
What needs 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.
For how long have I used the solution?
I started using Document Understanding six months ago.
What do I think about the scalability of the solution?
In the community version, there is a limit on data extraction using a form-based extractor. There are limitations on digitization in the community version. You can do only 50 or so in one hour. The enterprise version can handle a larger volume of data, but we aren't dealing with huge amounts of data. We can still use multiple types. It allows you to scale with multiple types of extractors in the same document. If I'm confident in how the model is processing a particular field, it can be adopted into the regular business structure and reused.
Which solution did I use previously and why did I switch?
How was the initial setup?
I was involved in the deployment only as a developer. We created the taxonomy and the model for Document Understanding, then tested multiple cases with multiple documents. We see which extractor would be the best fit for a particular value. We can classify it according to the values we want and we can set up an accuracy also. We can set a confidence level for each variable, so the confidence is different for a regular extractor versus a complex one. I set the confidence level high on the regular extractor.
Initially, the deployment is somewhat complicated for a developer. However, it gets easier once you understand everything. We didn't need a consultant. I could complete the job by myself. It isn't rocket science. UiPath Academy has a free course on Document Understanding. Anyone can use it for free.
What's my experience with pricing, setup cost, and licensing?
We use the free community version. Anybody can use it, but it has some subtle limitations. The enterprise license gives you far better results without limitations.
Document Understanding can handle handwriting and signatures in most cases. The community version limits handwritten document processing, but it's enough for our needs and gives us the correct data every time.
Which other solutions did I evaluate?
I haven't worked with any other document processing solution besides UiPath. I researched some tools, but Document Understanding seemed like the best fit for me, so I used it.
What other advice do I have?
I rate UiPath eight out of 10. I deduct two points because creating the configurations can be time-consuming.
Which deployment model are you using for this solution?
Public Cloud
Disclosure: PeerSpot contacted the reviewer to collect the review and to validate authenticity. The reviewer was referred by the vendor, but the review is not subject to editing or approval by the vendor.
RPA Developer at a computer software company with 51-200 employees
Helps extract images, signatures, and writing
Pros and Cons
- "UiPath Document Understanding's image file extraction feature is the best in any OCR solution."
- "The signature comparison feature of UiPath Document Understanding could be improved."
What is our primary use case?
I use UiPath Document Understanding to extract data from scanned images using OCR technology. For example, when we have invoices, we can extract data from them by creating a model for that particular template using OCR technology, artificial intelligence, and machine learning. Every invoice has its own template, so we can create a template model and implement it in UiPath to run a bot for the data extraction process. After extracting the data, we can store it in an Excel file or database, whichever we prefer.
We deploy UiPath Document Understanding in the cloud and then integrate it with our on-premises architecture using a single key.
How has it helped my organization?
UiPath can automate any repetitive task, such as data entry, data extraction, file downloading, and file uploading, in any financial services, banking, or health insurance sector. The document formats include tables and checkboxes.
It can extract handwriting and signatures as long as they are legible.
Machine learning capabilities can be used to retrain prebuilt models for use with other templates.
It has helped improve our organization by reducing human tasks and errors.
Whenever data is extracted from a document using UiPath Document Understanding, we receive a confidence level rating. If the confidence level is low, we send the extracted information to the Action Center for human validation.
UiPath Document Understanding does the work of three full-time employees.
Using UiPath Document Understanding for documents without business or application exceptions reduces human error by 100 percent.
What is most valuable?
UiPath Document Understanding's image file extraction feature is the best in any OCR solution.
What needs improvement?
The signature comparison feature of UiPath Document Understanding could be improved.
To my understanding, we can only integrate UiPath Document Understanding with UiPath. I would like the ability to integrate with other solutions.
For how long have I used the solution?
I have been using UiPath Document Understanding for two years.
What do I think about the stability of the solution?
UiPath Document Understanding is stable.
Which solution did I use previously and why did I switch?
We previously used an Excel automation tool but switched to UiPath Document Understanding because it is a better solution for repetitive tasks.
How was the initial setup?
The initial setup is straightforward. The deployment was completed by two people including myself.
What about the implementation team?
The implementation was completed in-house.
What's my experience with pricing, setup cost, and licensing?
We received a 60-day free trial before having to purchase a license to continue using UiPath Document Understanding.
What other advice do I have?
I would rate UiPath Document Understanding nine out of ten.
Data extraction accuracy depends on the document's quality and format. The maximum percentage of accurate data we can extract using UiPath Document Understanding is 90 percent.
We started to see the value right after implementing UiPath Document Understanding.
Which deployment model are you using for this solution?
On-premises
Disclosure: PeerSpot contacted the reviewer to collect the review and to validate authenticity. The reviewer was referred by the vendor, but the review is not subject to editing or approval by the vendor.
Vice President at a tech services company with 1,001-5,000 employees
It's scalable, but handwriting extraction is challenging
Pros and Cons
- "It is a pretty scalable tool, and it works well for big companies."
- "A lot of coding is required to make handwriting decoding happen; it's not so easy as plug and play."
What is our primary use case?
We use it for broker closure, KYC, mortgage processing, and invoice processing as of now.
We have about 100,000 invoices a year, 50,000 KYC applications, and another 100,000 for broker closures.
What is most valuable?
It is a pretty scalable tool. It works well for big companies.
What needs improvement?
The challenge is more on handwriting and language-specific document extraction. There is some room for improvement when it comes to understanding handwriting. Document Understanding at the current stage is moving some of their technologies to Agentic using LLMs to increase the accuracy of their extraction, so I still find there's a lot of room for improvement. For example, extracting information from engineering drawings will be a challenge, so we'll have to use a lot of AI technology to make it happen.
From the technology point, they are already working in the agentic space and trying to deploy more agents. I believe that enhancing their orchestration engine with an API-driven approach would be a great starting point for further development.
For how long have I used the solution?
I have been using UiPath Document Understanding for about five years.
How are customer service and support?
My experience with technical support of both UiPath Document Understanding and Blue Prism has been good. They can improve in terms of the response time and resolution of the issues.
How would you rate customer service and support?
Positive
Which solution did I use previously and why did I switch?
I have not used any other similar solution.
What's my experience with pricing, setup cost, and licensing?
Both UiPath and Blue Prism are expensive.
Customers are trying to move to some other Agentic space because of high pricing, so the new initiatives are put on hold, and they're looking for alternatives as well.
What other advice do I have?
I would recommend UiPath Document Understanding for big companies, not for small ones. A lot of coding is required to make handwriting decoding happen; it's not so easy as plug and play. It's all about putting in a lot of effort to make that work.
I would rate UiPath Document Understanding a five out of ten.
Which deployment model are you using for this solution?
On-premises
Disclosure: My company has a business relationship with this vendor other than being a customer. Partner
Last updated: Oct 13, 2025
Flag as inappropriateRPA Developer at a tech services company with 10,001+ employees
Helps reduce human error, can handle multiple document formats, and can be trained
Pros and Cons
- "The most valuable feature is the ability for humans to train the bot."
- "The extraction and classification process should be simplified."
What is our primary use case?
UiPath Document Understanding allows us to extract information from documents, classify the document type, and optionally validate the data with a human. We also train the bot to learn from the mistakes it makes.
We extract data from boxes and tables, as well as handwritten words.
How has it helped my organization?
UiPath Document Understanding helps us extract from certificates, the names, addresses, states, dates, taxpayer identification numbers, and signatures. We also extract information from health insurance documents such as the name, patient's address, code, and contact information. Additionally, we have invoices that we have to extract from a table with rows.
UiPath Document Understandings' ability to handle different document formats depends on which extraction tool we use and the clarity of the documentation.
I am very satisfied with UiPath Document Understanding AI and machine learning.
UiPath Document Understanding integrates well with other tools. Some of my colleagues have integrated the solution with ABBYY.
It has helped reduce human error.
What is most valuable?
The most valuable feature is the ability for humans to train the bot. It can learn from human experience, so if we include steps in our framework for humans to validate extraction or classification, the bot can learn from them to improve document understanding and precision in future document processing.
What needs improvement?
The extraction and classification process should be simplified.
For how long have I used the solution?
I have been using UiPath Document Understanding for six months.
What do I think about the stability of the solution?
UiPath Document Understanding is stable.
What do I think about the scalability of the solution?
UiPath Document Understanding is scalable.
How are customer service and support?
The technical support is good.
How would you rate customer service and support?
Positive
How was the initial setup?
The initial deployment was straightforward. The deployment took three hours to complete.
What about the implementation team?
I implemented the UiPath Document Understanding myself.
What other advice do I have?
I would rate UiPath Document Understanding eight out of ten.
Our organization also uses ABBYY.
We saw the time to value within the first three days of using UiPath Document Understanding.
Which deployment model are you using for this solution?
Public Cloud
Disclosure: PeerSpot contacted the reviewer to collect the review and to validate authenticity. The reviewer was referred by the vendor, but the review is not subject to editing or approval by the vendor.

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Updated: September 2025
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Thank you for your valuable review Biswajeet.