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RPA Developer at Arkon Group LLC
Real User
Reduces human validation, offers good machine learning and has excellent document understanding
Pros and Cons
  • "It's great for document understanding for invoices and installments."
  • "It would be ideal if they could include more packages for more use cases."

What is our primary use case?

I've done multiple projects. A couple of them included invoice processing. It has a machine learning package that works out of the box. For invoices. I use that. It does a very good job. 

I also use document understanding, which doesn't have any training. I trained it for the extraction of data for some forms like car loan installments. It did a pretty good job. 

In addition, I used it for a medical department. I use document understanding. 

How has it helped my organization?

We wanted to have a way to do data extraction from PDF documents. It helped us automate the process. For example, if you purchase a car, the loan installment paper includes items like the vehicle number, purchase information, buyer and seller information, et cetera. It can pull that out. We can also use it similarly in the healthcare industry, to get client details. 

What is most valuable?

It's great for document understanding for invoices and installments. 

When it comes to document understanding for handwriting, it does a decent job sometimes with handwriting, however, some people have weird handwriting and the OCR can struggle to pick up the information. In those cases, you have to read it yourself. However, overall, it does a decent job. I haven't used it to read checkboxes or bar codes. It works well with tables, however.

There are thousands of documents that are completely, automatically processed. It can process close to a few thousand invoices per day.

I also integrated it with the Action Center for some projects; It's pretty neat.

I like the machine learning skills and the fact that they come out of the box. They are packages that you can just deploy. The training of the ML is great; there is this tool that comes with it called Data Manager. That's very handy when you are labeling data and then using it. 

The AI center is excellent. AI does a pretty good job covering all the needs that are needed for automating the process for semi-structured documents. The structured documents with the form extracted, overall, are pretty good. It's doing a very impressive job. I was surprised the first time I was exposed to it. Now, I actually enjoyed doing it. It allows me to automate items that are mundane. For example, if an employee is given a task to scrape data from invoices, which are PDFs, they can get the robot to do it. Due to the fact that the documents most of the time are semi-structured, machine learning can handle the task, and machine learning is doing a pretty good job of handling that instead of the employee.

I've used Forms AI. So far, my experience has been pretty good. That said, it only works for structured documents. 

In terms of the documented understanding of integrating with other systems or applications, everything is good. You can integrate it with the action center, and it does a very good job. Everything is handy and easy to use. Integration overall is good.

Human validation is not always required for the outputs. It depends on the document. For invoices, you might need human validation 5% to 10% of the time. If it processes ten documents, I would expect one document at least to need human intervention. If you are building some custom ML skills for some documents, if the document itself is scanned well and positioned well, it does a pretty good job of extracting the needed fields. If it's slightly less quality then the robot will struggle with both the OCR or extracting and digitizing data. Overall, we might need 10% to 20% human validation. The validation process itself now takes about a minute with the help of automation. It's reduced everything by a minute or two to up to five or six minutes. 

Document understanding has helped us to reduce human error by at least half.

What needs improvement?

The only problem that I can see with integration is some of the features cannot be used inside the loop. At least that was the case before. I don't know if they fixed it or not. You can't put some of the activities that are de-related inside the loop. It's going to throw an error if you do.

It would be ideal if they could include more packages for more use cases.

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.

For how long have I used the solution?

I've used the solution for about a year. 

How are customer service and support?

I've contacted technical support and they have been helpful. 

How would you rate customer service and support?

Positive

What other advice do I have?

I'm a customer and end user. I work as a developer. 

I'd rate the solution nine out of ten overall. 

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.
PeerSpot user
Anudeep Gill - PeerSpot reviewer
Senior Consultant, Digital Transformation at ZINNOV MANAGEMENT CONSULTING
Consultant
Helps reduce human error and provides great document classification, but the AI has room for improvement.
Pros and Cons
  • "Document classification is very good."
  • "UiPath Document Understanding can improve its handwriting and signature recognition."

What is our primary use case?

We use UiPath Document Understanding for P2P processes to extract document information for ingestion, processing, and classification.

The key problem our clients faced, which we were trying to solve by implementing UiPath Document Understanding, was the large amount of unstructured data in the events. They want a solution that can solve this problem right from the beginning, from the document ingestion phase to the document classification and streamlining the document for the data taken right inside the documents. So driving all those analytics and the ROI in the end is a major key asked by most of our clients.

Our clients deploy UiPath Document Understanding both on-premises for our banking clients and also on the AWS cloud for others.

How has it helped my organization?

UiPath Document Understanding has helped us automate a large number of accounts payable processes for our clients such as P2P and O2C. 

It helps us process many types of file formats primarily PDF. We are able to process a large volume of documents using UiPath Document Understanding.

In our P2P process, we have encountered some handwritten invoices. The handwriting text recognition feature offered by UiPath is good, and it has been very helpful in converting these handwritten documents to a more structured format. Apart from handwritten invoices, there are other documents that require extensive merging and sorting, which has always been a concern for many of our clients. I believe that UiPath has effectively solved this problem.

Our clients process over 90% of documents using UiPath Document Understanding are processed straight through without human validation.

When we use Document Understanding to analyze data, the AI works in the background to process the document seamlessly.

The ability to integrate with other systems and applications is really great. I would rate it a nine out of ten.

It has improved our clients' cost savings and time savings, in turn improving productivity and providing a better ROI.

The time required to manually validate information depends on the type of document. A handwritten document takes longer than a PDF file and can take up to half an hour.

The average handling time has improved and is now under ten minutes.

It is very effective at reducing human error in identifying incorrect fields in documents. This is where I think it excels. We have seen a reduction in human errors by up to 90 percent.

UiPath Document Understanding has helped free up staff time for other projects.

We typically see a time to value after four to five days from starting the process, but again, this depends on the process.

What is most valuable?

Document classification is very good. We have received great feedback from customers who use it to classify bank documents, sort them, and generate formal documents. I think the overall presentation of the final document is amazing.

What needs improvement?

UiPath Document Understanding can improve its handwriting and signature recognition. We have also been engaging with other intelligent document processing companies such as ABBYY and Kofax, which have superior features for handwritten text recognition. UiPath offers a good solution, but ABBYY has far more support for handwritten text recognition, especially in the latest version.

It is still in its infancy and has room for more advanced AI features.

They need to strengthen their relationships with IDP partnerships.

They should expand its library.

For how long have I used the solution?

I have been using UiPath Document Understanding for almost six months.

What do I think about the stability of the solution?

UiPath Document Understanding is a stable solution that our clients are comfortable using.

What do I think about the scalability of the solution?

UiPath Document Understanding is highly scalable if I want to extend support to the maximum number of subprocesses within a single process. Therefore, I believe there is no scalability issue.

How are customer service and support?

The support is good but sometimes the response time is slow.

How would you rate customer service and support?

Neutral

How was the initial setup?

The initial deployment complexity depends on the document. Therefore, we must be cautious when integrating with third-party vendors. I believe it takes more time to deploy critical documents with sensitive data. We must be very careful when choosing a vendor, such as AWS or Azure, to ensure that we can integrate with them successfully.

We use a team of three to four people for Document Understanding deployments.

What's my experience with pricing, setup cost, and licensing?

UiPath is more expensive than ABBYY and Kofax.

Our clients are concerned about the volume-based pricing model, as UiPath charges more than other vendors in the market.

What other advice do I have?

I would rate UiPath Document Understanding seven out of ten.

UiPath Document Understanding requires maintenance from time to time, and we are currently experiencing a slowdown in the oral solution. Therefore, I believe that maintenance is required. Perhaps they need to develop a newer, more intelligent, and more efficient version, as Kofax and ABBYY have done. The same team of people that deploy UiPath Document Understanding also handles the maintenance.

There are other vendors who are excelling further in the intelligent document automation space. They offer more advanced capabilities and AI intelligence than Document Understanding, which is still an evolving solution. When we read customer reviews and have first-time conversations with clients, we notice that they often start by naming vendors like ABBYY, which are known for their technical expertise in the IDA space.

Disclosure: My company has a business relationship with this vendor other than being a customer. consultant
PeerSpot user
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.
reviewer2290032 - PeerSpot reviewer
Sr Software Developer
Real User
Offers multiple types of extractors, saves us time, and reduces human errors
Pros and Cons
  • "UiPath Document Understanding offers multiple types of extractors, which we can use to extract information from documents in a variety of ways."
  • "UiPath Document Understanding has difficulty identifying handwritten documents, and there is room for improvement."

What is our primary use case?

I use UiPath Document Understanding to extract data from digital invoices.

We implemented UiPath Document Understanding to eliminate the need for manual invoice data extraction.

We process 50 invoices per day for a logistics organization. We receive the invoices from the user, and a bot reads them one at a time, extracts the details and stores them in an Excel file. If the extraction does not match the confidence score, we send the invoice to the Action Center for manual validation. Once the data is extracted, the bot enters it into SAP and validates it against the system information.

How has it helped my organization?

We used machine learning to train a model to process the different formats we were receiving.

Seventy percent of the documents we process are completed automatically without any manual intervention.

The AI and machine learning capabilities of UiPath Document Understanding are good.

Once trained on a large dataset, AI can save us significant time by performing tasks that are beyond our capabilities.

Human validation is required for about 25 percent of the documents we process. For smaller documents, it takes a human a few minutes to validate the information.

Our average handle time after implementing UiPath Document Understanding is five minutes.

UiPath Document Understanding has helped reduce human error.

UiPath Document Understanding has helped free up our staff time.

We can see results as early as two months, and definitely by six months.

What is most valuable?

UiPath Document Understanding offers multiple types of extractors, which we can use to extract information from documents in a variety of ways. Machine learning is a particularly useful method, as it allows us to train custom models to meet our specific needs.

What needs improvement?

UiPath Document Understanding has difficulty identifying handwritten documents, and there is room for improvement.

Some of the invoices we process are stamped, and the AI has difficulty understanding them because the stamp format varies between a square and a circle. Resolving this issue will allow us to process more complex documents using UiPath Document Understanding.

For how long have I used the solution?

I have been using UiPath Document Understanding for one year.

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.

What other advice do I have?

I would rate UiPath Document Understanding eight out of ten.

The solution was deployed in a single department for multiple users.

Maintenance is required for continuous training whenever an invoice format changes or a new vendor is added.

I recommend conducting a POC with the community to ensure that UiPath Document Understanding meets the organization's requirements before fully implementing it.

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. The reviewer's company has a business relationship with this vendor other than being a customer: Integrator
PeerSpot user
RPA Developer at a non-tech company with self employed
Real User
Reduces development time and improves productivity and accuracy
Pros and Cons
  • "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."
  • "There could be a feature similar to ChatGPT where when you ask about a document, you get an answer about what is there in that document. If possible, this kind of feature can be incorporated so that you do not need to open a file and take the value. It should directly detect that instead of opening and validating the document. Such a feature will speed up the process."

What is our primary use case?

I have been using it for processing invoices, receipts, and multiple forms of documents. We have structured and unstructured documents. Structured documents include forms, and unstructured documents include written documents and receipts. For identifying the type of document and for processing those documents, we use UiPath Document Understanding. It helps to identify the type, extract the information, and process the information.

How has it helped my organization?

We are able to process multiple documents and extract information from them. We can put that information into an Excel or a PowerPoint file. We can also put that on a website or in an application such as SAP. We can generate a PDF. We can do all this with UiPath Document Understanding. So far, I have only exported information into an Excel file. I have not integrated it with any other system.

UiPath Document Understanding can extract information from unstructured or handwritten documents. It can extract information from structured documents such as forms. It can process invoices. I have mostly tried it with structured documents, and I have not had any problems with it.

UiPath Document Understanding makes the work easy. It can classify a document and capture the information. It is able to process a document quicker than a human. Its AI and ML capabilities improve productivity and accuracy. If we have a lot of invoices of a certain pattern, we can feed that pattern. It can then process multiple documents of that pattern. This way machine learning helps us to easily process more documents.

We can now design or develop a process much faster. Previously, we had to do string manipulation to extract information from invoices, which required a lot of coding knowledge, but with UiPath Document Understanding, that is not required. It automatically identifies the type of document and extracts information. It saves time and improves accuracy. It is a low-code or no-code solution, and even someone who is not skilled in programming can design a process. From half an hour to one hour, process designing now takes 10 to 15 minutes. 

Human validation is required for certain business processes. The Present Validation Station activity enables you to review and confirm whether correct values are extracted or not.

UiPath Document Understanding reduces human errors. Humans can make mistakes while extracting information or while coding. To avoid all those problems, we are using UiPath Document Understanding. It helps us reduce human errors because no coding is involved. We are directly teaching the system how to identify a document. It automatically identifies a document and extracts information from it. Because the system does that by itself, we can reduce a lot of human error. There is a 40% to 50% reduction.

What is most valuable?

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.

What needs improvement?

There could be a feature similar to ChatGPT where when you ask about a document, you get an answer about what is there in that document. If possible, this kind of feature can be incorporated so that you do not need to open a file and take the value. It should directly detect that instead of opening and validating the document. Such a feature will speed up the process.

For how long have I used the solution?

I have been using this solution for the past two or three months. I have been using it only for practicing. I am not using it for any industrial purpose.

How are customer service and support?

UiPath is giving very good support. They also have some webinars, which are very helpful in developing our solution. I would rate their support a nine out of ten.

How would you rate customer service and support?

Positive

Which solution did I use previously and why did I switch?

Before UiPath Document Understanding, I was using string manipulation and screen scraping methods for extracting values from invoices. It used to take more time to build a solution. 

How was the initial setup?

It is deployed on-prem. Its deployment was straightforward. It took 10 to 15 minutes.

In terms of maintenance, bots require some maintenance. Bots can fail, so continued maintenance may be required.

What about the implementation team?

I deployed it myself. I am using it on my own.

What's my experience with pricing, setup cost, and licensing?

I have only been using its free version.

What other advice do I have?

It is a very good solution. It improves productivity and accuracy. It reduces development time.

You can use UiPath Document Understanding even when you do not have programming knowledge. You just need to know the pattern of documents. It has ML capabilities, and the bot will automatically learn and start to identify and process documents. It is very easy.

Overall, I would rate UiPath Document Understanding a nine out of ten.

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.
PeerSpot user
Mikolaj Zielinski - PeerSpot reviewer
Senior Software Engineer in Intelligent Automation at Bayer
User
Speeds up our data analysis and improves data quality
Pros and Cons
  • "One of the most valuable features is the intelligent recognition of the fields. The algorithm is able to recognize them based on the pattern. Also, the machine learning model enables you to use predefined solutions. The machine-learning capabilities of the solution are very cool."
  • "The documentation should be more clear, or better training should be provided."

What is our primary use case?

We have processes for purchase orders. We need to analyze the content of these files and some invoices. Based on that, we are able to perform qualifications and post them to the CRM system. Overall, we call this our invoice control process.

We wanted to optimize the performance, meaning the time the process takes, and the quality. We had some problems with the quality of transferring the data because people would make mistakes. If they were doing 80 documents per day, there was a high possibility that they would forget to look for some information or they would copy and paste the wrong fields.

How has it helped my organization?

The main benefit for us has definitely been a faster process. We have sped up the process of analyzing the data. A second one is the improvement in the quality of our implementation.

In our organization, we are now at 30 percent of our documents being completely processed automatically. And in terms of human validation required for output from Document Understanding, we need it for 15 percent of the cases. We have decreased the time needed for such processing by 70 percent. And regarding human error, we have seen a decrease of about 60 percent.

What is most valuable?

One of the most valuable features is the intelligent recognition of the fields. The algorithm is able to recognize them based on the pattern. Also, the machine learning model enables you to use predefined solutions. The machine-learning capabilities of the solution are very cool. I really like that part, and I hope it will be developed even more in the future. I'm really excited to see how it will develop.

Integrating Document Understanding with other systems and applications is very easy if you already have some background. It just requires some mature developers to do so, and we are just about at that stage. It's very user-friendly, but the documentation could be a little more detailed. Besides that, it is fine.

What needs improvement?

With handwriting, we had a problem. It wasn't able to extract it because we have handwritten documents in Polish, and that language is not supported at this time.

Also, the documentation should be more clear, or better training should be provided.

For how long have I used the solution?

We have been working with UiPath Document Understanding for about eight months.

What do I think about the scalability of the solution?

Scalability is very easy to manage. It's very natural. The only thing that changes is the number of processes and the number of licenses. The more money we save with it, the bigger we will scale it.

We are using it across four departments.

How are customer service and support?

I really like their customer support. They are very responsive.

How would you rate customer service and support?

Positive

Which solution did I use previously and why did I switch?

We had ABBYY. The advantage we see with UiPath is that it's easier to implement things with RPA. Some of our teams are still using ABBYY, but our team has declined to use it anymore for automation.

How was the initial setup?

I'm the system owner and architect, so it was on me to set it up. The initial setup was very complex in the sense that we had to play with the firewalls and other things to make it work.

It included the entire cloud, not only Document Understanding. It was very tricky to do it the correct way. We had to do a lift-and-shift. We updated the on-prem environment to the latest possible version and then copied the entire base to the cloud. Later, we upgraded each process, and, once the process was upgraded and ready to work in the cloud, we moved it to the target tenant.

At this moment, it does not require any maintenance.

What about the implementation team?

We did it ourselves. We had a team of 20 people, but that's because we have a lot of processes.

What was our ROI?

We will need to have the solution for at least one year to have a clear view of ROI. It's the same for time-to-value with the solution.

What's my experience with pricing, setup cost, and licensing?

It's expensive, but you can reduce the price per license by getting more licenses. Overall, the pricing is okay.

One area for improvement would be a different licensing model. Right now, we have to assign a license to allow a user to do validation. We think that standard access to Orchestrator should allow a user to validate.

What other advice do I have?

Definitely talk first with a UiPath representative to get someone who will take care of you and the implementation. Do not waste your time reading through the documentation because it's very messy.

Which deployment model are you using for this solution?

Public Cloud
Disclosure: My company has a business relationship with this vendor other than being a customer. Partner
PeerSpot user
Business Head for Syber Security at One Networks
Real User
Top 10
Helps free up time, reduce human error, and automate processes
Pros and Cons
  • "The prebuilt algorithm for extracting foreign invoices is the most valuable feature because it eliminates the need for us to build anything from scratch."
  • "The signature and handwriting are a pain point for the OCR and have room for improvement."

What is our primary use case?

We are a system integrator in the manufacturing industry and our clients use UiPath Document Understanding for their invoicing cycle processing.

Previously, our clients manually entered invoices into their systems, seeking a solution to automate this process while still maintaining controls for verification and audit purposes. We implemented UiPath Document Understanding to address this need.

How has it helped my organization?

Data entry is the most common use for UiPath Document Understanding.

In Italy, a common document format for simplified sales invoices is the BBT, which lists the total cost of the entire merchandise unit.

Since our clients are primarily small and medium-sized businesses, UiPath Document Understanding processes around 10,000 documents annually.

The documents contain a header and a large table where data is extracted.

Around 30 percent of the documents are fully completed by UiPath Document Understanding.

AI and machine learning do a great job sorting and identifying fields and documentation orientation. Managing different layouts is the most valuable attribute of AI.

Companies that use the UiPath platform can easily integrate UiPath Document Understanding using a few modules.

Human validation is required for 20 to 30 percent of cases and it takes less than one minute to complete.

UiPath Document Understanding helps reduce human error by 70 percent.

UiPath Document Understanding has helped free up around 70 percent of people's time to work on other projects.

For most of our clients, the time to value is usually six months.

What is most valuable?

The prebuilt algorithm for extracting foreign invoices is the most valuable feature because it eliminates the need for us to build anything from scratch.

What needs improvement?

The signature and handwriting are a pain point for the OCR and have room for improvement.

The extraction logic portion of the UI is not as user-friendly as the rest of the platform and has room for improvement.

I would like to have generative AI integration added to a future release.

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?

The stability of UiPath Document Understanding is good. The higher the stability the less maintenance is required.

What do I think about the scalability of the solution?

The scalability can be improved with the help of generative AI. It is difficult to build an algorithm and move to another project without making important changes to it.

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 process is not user-friendly. It requires a lot of steps, although depending on the size of the deployment, one person can usually manage it.

The average deployment takes around one month to complete. 

What about the implementation team?

We implement the solution for our clients.

What's my experience with pricing, setup cost, and licensing?

The price for UiPath Document Understanding is a bit expensive.

What other advice do I have?

I would rate UiPath Document Understanding a nine out of ten.

The number of people required for maintenance depends on the project. It can go from one person up to seven.

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?

Other
Disclosure: My company has a business relationship with this vendor other than being a customer. partner
PeerSpot user
reviewer2293893 - PeerSpot reviewer
Mrs at a manufacturing company with 11-50 employees
Real User
Gives us a complete, unattended process for extracting details from PDFs, saving us hundreds of hours
Pros and Cons
  • "In UiPath Document Understanding, I use two extractors. One is the Intelligent Form Extractor and the other is the Machine Learning Extractor. The first one is very useful and user-friendly. When we have a single template or two to three templates, Intelligent Form Extractor is much easier to use. But if we have multiple templates, it's better to go with ML Extractor as you can train the model with different templates."
  • "There are also problems with handwritten documents. The results from those are not 90 percent accurate. With scanned and native PDFs, it is 90 to 99 percent accurate, but the accuracy of handwritten documents is somewhat less. If they could improve on that, it would also be helpful."

What is our primary use case?

Our use cases are in the banking sector. We have certain PDFs that contain customer data, and we have to extract data from them and compare it with the data provided earlier. The PDFs can be scanned, handwritten, or native PDFs.

How has it helped my organization?

It gives us a complete, unattended process for extracting details from PDFs. Otherwise, that would been redundant work done by specialists. It is saving us around 800 workers.

For one record, we used to take about half an hour, but Document Understanding completes things in seconds. It's very quick. It has also reduced human error a lot.

What is most valuable?

In UiPath Document Understanding, I use two extractors. One is the Intelligent Form Extractor and the other is the Machine Learning Extractor. The first one is very useful and user-friendly. When we have a single template or two to three templates, Intelligent Form Extractor is much easier to use. But if we have multiple templates, it's better to go with ML Extractor as you can train the model with different templates.

The artificial intelligence features are very good. The more you train it, the more you will benefit from it.

Also, integrating Document Understanding with other systems or applications is not complex. It's quite easy. Even for attended processes, if you combine UiPath Document Understanding with Action Center, it's almost like unattended processing.

What needs improvement?

Document Understanding is a combination of the extractor and OCR. Depending on the taxonomy that you give and the classification that you define, it is accurate. But there are multiple OCRs and I find UiPath Document Understanding to be as accurate as Microsoft or Textract OCR. If the accuracy was improved, it would be much better.

There are also problems with handwritten documents. The results from those are not 90 percent accurate. With scanned and native PDFs, it is 90 to 99 percent accurate, but the accuracy of handwritten documents is somewhat less. If they could improve on that, it would also be helpful.

Also, in the banking sector, we can't use the cloud-based Orchestrator or cloud endpoints for OCR. Getting approval for ML Extractor takes a lot of time for us. Instead, if we could go with Intelligent Form Extractor, it would save a lot of approval time. If they could improve and add features to Intelligent Form Extractor, it would make our lives easier.

For how long have I used the solution?

I have been working with UiPath for five and a half years and with Document Understanding for one and a half years.

What do I think about the stability of the solution?

I have not experienced it crashing or lagging.

What do I think about the scalability of the solution?

The scalability is good. I haven't seen any waste of money.

How are customer service and support?

We have not contacted their technical support very much.

How was the initial setup?

We do not use UiPath in the cloud; we have our own internal version, so the initial setup took time for us. But that had nothing to do with UiPath. It was because of our company's policies.

It took time for people to understand it, but once they got it, it went well.

What was our ROI?

It took some time because Document Understanding is pricey compared to other tools in UiPath. After 10 to 15 days, when there were fewer errors, that's when we started to see profits.

What other advice do I have?

I would suggest combining other technologies with UiPath. That's when you see more benefit from Document Understanding.

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.
PeerSpot user
reviewer2274936 - PeerSpot reviewer
Assistant Consultant-Software Development RPA Technology at a tech services company with 10,001+ employees
Consultant
Helps simplify our process and reduces human validation and errors
Pros and Cons
  • "There are many features that can be added to the action center to keep humans in the loop to evaluate the accuracy of the extracted data."
  • "UiPath Document Understanding could be more user-friendly."

What is our primary use case?

We use UiPath Document Understanding to extract data from invoices so that the data can be entered into SAP applications. We often receive multiple invoices in different formats. To use UiPath Document Understanding, we need to train the document. This means that we need to provide a sample template that the robot can use to learn how to read the invoices and extract the desired data. The labels in the fields are important, as they tell the robot what information to extract. 

For example, the invoice number, seller's address, quantity, and any other required information. The table of line items also needs to be extracted. We define the fields from which we need to extract data. We use the form-based extractor or machine learning extractor to extract the data. We export the extracted data to an Excel file. This allows us to collect all of the data from multiple invoices in a single location. We can also implement a validation step to ensure that the robot has extracted the data correctly. This can be done easily by using the human in the loop to manually review the extracted data before it is entered into SAP applications.

How has it helped my organization?

Our organization has many invoices of varying formats. To simplify the process, we implemented UiPath Document Understanding to extract the required data from all the unstructured invoices and import it into a single, structured Excel sheet.

Using the different endpoints and machine learning, we can extract data in different formats including handwriting and signatures.

UiPath Document Understanding's machine-learning capabilities are good. We use it to extract the information we need from documents of any format, and then align it with the corresponding table.

We easily integrated UiPath Document Understanding with UiPath Studio by connecting the data flow from the different applications to extract the necessary records.

We have so many invoices that UiPath Document Understanding helps us classify them. The document is first classified into a type of document, such as an invoice or a resume. This segregation of data allows us to send the invoice templates to our folder and extract the data and all the details without having to read them one by one.

With UiPath Document Understanding, less and less human validation is required over time. Each time we run the process, we can select from an option for attended or unattended automation. The other option is to use the confidence score to determine whether human validation is required.

The handling time before automation for one PDF document was five minutes and now with automation, it is one to two minutes.

UiPath Document Understanding helps to reduce human error by removing the fatigue factor and by continuing to run after hours without breaks.

What is most valuable?

There are many features that can be added to the action center to keep humans in the loop to evaluate the accuracy of the extracted data. We can also set a confidence score threshold, such that if the confidence score is greater than 80 percent, we can take a certain action. Otherwise, we need to manually correct the problem in the action center.

What needs improvement?

UiPath Document Understanding could be more user-friendly. There are so many endpoints, and entering the API is also a manual task. Currently, it is a long and complicated process with many steps. If we remove all of those steps and use the ChatGPT or OpenAI library, we can start using the solution with fewer steps.

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 can be scaled for multiple invoices.

How was the initial setup?

The deployment was straightforward and required a few days.

What other advice do I have?

I would rate UiPath Document Understanding eight out of ten.

We are processing around 12 documents using UiPath Document Understanding. The documents are in PDF format.

We have four members using the solution.

Which deployment model are you using for this solution?

On-premises
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