UiPath IXP Reviews

By implementing UiPath Document Understanding, we wanted to extract data from the documents, specifically native PDF documents. 

In terms of integration, we have integrated it with SAP. 

We are processing 100 to 150 invoices of 20 to 30 pages, totaling around 1k pages in a month, and the document format is PDF. Our organization's documents are completely processed automatically if there is no change in the template, but if there is a slight change in the invoice template, then they aren't processed automatically.

Validation does not take much time because we have developed an application that allows us to validate by modifying the data in the database while viewing the PDF image and extracted text. Human validation is required for at least 2 out of 10 invoices. The human validation process may take approximately 10 minutes per document, but it depends on the number of pages.

Before automating our process with UiPath Document Understanding, the average processing time was in hours, but now, after validation, it takes just 5-6 minutes.

UiPath Document Understanding has helped reduce human errors to some extent. The extraction of data should be accurate to avoid manual validation. 

UiPath Document Understanding has helped to free up staff's time for other projects, but the cost is high. In India, costs are increasing, and we are looking for cost-effective solutions. We are trying Agentic AI solutions to reduce costs, as every year the license cost of UiPath Document Understanding increases. 

Regarding time savings, 1-2 hours are reduced to 5-6 minutes.

Pre-trained models are valuable, and they work well. UiPath Document Understanding has pre-defined sets of trained models. We are using those and training our invoice templates, so we are using the pre-trained templates, and we are able to extract data based on our needs.

We have to do manual validation for some of the things due to the OCR engine not being so accurate. For example, S is read as 5, 5 as S, 2 as Z, and Z as 2. In the case of currency, if one dot is missing, it gives a completely incorrect number.

These discrepancies should be fixed because if the OCR itself doesn't work properly, then AI doesn't help with that. When AI is used for training models, the AI Center works precisely, but if the data itself is wrong, we can't do anything. If the extraction of data is proper, it definitely helps. However, 20% errors could be reduced if the OCR engine were better. In future updates, I would like to see better handling of issues such as when a dot is missing in currency, for example, with dollars, it should handle that automatically.

It's very expensive. If the volume increases, we can't afford to use Document Understanding. We are thinking of moving to another solution because we are expecting 80,000 to 100,000  invoices.

My overall experience with UiPath Document Understanding is for more than 3 years.

It is stable.

UiPath Document Understanding is scalable. We are not planning to increase the usage of UiPath Document Understanding. We are trying to find alternative solutions as the volume is expected to increase, requiring more bots, which would increase costs.

In the initial days, we interacted with them, but we now find solutions ourselves. At the time, there was a delay in response. Our system is healthcare-related and needs to function 24/7, so we don't have the bandwidth to rely on the technical team's response times.

Neutral

The initial deployment was straightforward and took a few hours.

I was personally involved in the deployment process of the automation. Our implementation strategy involved deploying it in two environments: staging and production. We process invoices in the staging environment first, then confirm them before pushing to production. We use GitHub for code management. We create branches and push the updated code without impacting others.

For deployment, we didn't use any third-party integrators or consultants. We used GitHub and Jenkins schedulers, avoiding additional costs due to licensing expenses of those tools. For the process, a couple of resources are needed, specifically 16 developers are involved.

It definitely saves time. However, there are alternative solutions at lower costs.

We can use a simpler solution. We can use a Python script that converts PDF to text with 100% accuracy. There are other solutions that are free. We are planning to migrate to those.

It is expensive. The license cost for UiPath Studio has risen to around 3.5 lakhs last year, and I am uncertain how much the increase will be this year. They have also increased the bot prices. 

There are no additional costs; there is no extra cost aside from the standard licensing fee.

Before choosing UiPath Document Understanding, we evaluated other options like Automation Anywhere. We chose UiPath instead of Automation Anywhere because it is an on-prem solution suitable for governmental projects, like defense organizations.

My overall rating for UiPath Document Understanding is a four out of ten. It's good in technical aspects, but it's not cost-effective. 

The main use case is document automation. We have done everything from medical forms to supplier quotes, invoices, PO invoices, check requests, expedited invoices, utility invoices, expense reports, reimbursements, and things of that nature.

The documents we are processing are as low as 20,000 a year and as high as 2 million a year. They are as complex as you could humanly imagine.

What I appreciate most about UiPath Document Understanding is that it's a good introduction tool for customers to use, and it can be deployed quickly. UiPath Document Understanding, while good, is a very good IDP out of the box. You need to invest significant time to make it great, and you are probably better off integrating other tools with it to get to that level. The best thing about it is that it is decent out of the box. 

You can certainly configure it to help with human error. You can set up rules to do basic value checks and even route for human escalation.

The downsides are that it's wildly overpriced. The other players in the industry are catching up quickly, and if you really want it to be good, you probably need to augment its answers with those of another tool, whether that be Textract, Computer Vision, or another AI tool. It does not integrate smoothly with these solutions. I have to build custom integrations.

I have significant experience with UiPath Document Understanding.

We have used many different IDPs before. We've used Hyperscience, ABBYY, AWS Textract, and so forth.

UiPath is more expensive than ABBYY, and Hyperscience is more expensive than UiPath. In terms of what they try to do, their core value proposition is the same. ABBYY probably has slightly better, or at least did have slightly better, out-of-the-box capabilities for the price. Whether that remains true now, I'd have to study it. Hyperscience was supposed to have some automation with their tool. They overpromised and underdelivered. They were supposed to be what UiPath Document Understanding is, and I don't think they've achieved that, though maybe they have now.

We can deploy it quickly. UiPath is a very flexible platform that allows for customization.

We use agentic automation in this product. People are looking to automate more complex tasks, judgment-based tasks that are too complex for RPA to handle. This could be something as simple as generating a custom email for a potential client, doing outreach or quote follow-up, or as complex as setting up a remediation plan for reconciliation policy monitoring.

Regarding automatic document processing, invoices can have a 90% successful extraction rate, but with business rules, automatic processing reduces to 70%, which is intentional. The system can be configured to help with human error through basic value check catching and routing for human escalation.

Human validation requirements vary between 5% to 40% of the time, depending on how clients want to configure their tool.

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

UiPath Document Understanding is primarily used for invoice and document processing through optical character recognition (OCR). The team utilizes this technology to digitize quotes and orders from customers, extracting relevant details and updating our systems, including SAP.

UiPath Document Understanding cuts down a lot of order processing time and agents' time. They don't have to manually enter numbers into the system. This saves both human effort, which in turn translates to better cost efficiency.

It has many connectors and is considered an industry standard. Therefore, it works well with regular applications. For legacy systems, we utilize RPA and other solutions.

The accuracy of the solution is pretty good, and it offers flexibility in handling various types of documents. Most of the documents processed are in PDF format, but it also supports JPEG files. Overall, it does a decent job of highlighting and processing both PDFs and JPEGs.

UiPath Document Understanding provides capabilities for handwriting as well as PDFs and JPEGs. It does a decent job.

For UiPath Document Understanding, there is a possibility for improving accuracy with multilingual documents, especially handwritten ones. It doesn't have very great accuracy, particularly for handwritten documents and multiple European languages. They have to improve their accuracy of the models with UiPath Document Understanding.

They have to improve their accuracy of the models with UiPath Document Understanding. They are exploring agentic and other things, and they are keeping up with developments.

We have been using UiPath Document Understanding for the last three years.

It's pretty stable.

It's scalable.

Their technical support is very good.

Positive

It is easy to deploy.

We get around 60% to 65% accuracy with UiPath Document Understanding. The other 30% requires human validation. 

Approximately 60% of our company documents are completely processed automatically through straight-through processing (STP). 

Within six months of implementing, UiPath Document Understanding started yielding value and savings.

It can be cheaper, but for the work it does, it's decent. It's not a very affordable solution.

With a lot of LLMs and developments rapidly evolving, there are indeed some cheaper options. However, if you want an enterprise-grade, stable solution, then UiPath is definitely a choice.

I would rate this solution an eight out of ten.

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.

It is a pretty scalable tool. It works well for big companies.

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.

I have been using UiPath Document Understanding for about five years.

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.

Positive

I have not used any other similar solution.

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.

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.

The main use case for UiPath Document Understanding is extracting data from invoices. This invoice data needs to be fed into other ERP systems.

I have worked on two projects with UiPath Document Understanding. One involved a structured format with both scanned and electronic documents. The other project involved an unstructured format with approximately 20 different formats. For these formats, we created our own custom ML model. We trained the model on the documents and formats, allowing UiPath Document Understanding to categorize and classify incoming documents and use the appropriate ML model to extract data.

For RPA automation professionals, it is very easy to extract documents using UiPath Document Understanding. There are predefined ML models available in UiPath Document Understanding. Another interesting feature is that we can create our own ML model to utilize. Recently, they have introduced GenAI, which allows us to extract documents even faster and without hurdles.

Handwriting recognition in UiPath Document Understanding is very difficult. It is particularly challenging to fetch handwriting, government official seals, or authorized signatures. When working with UiPath Document Understanding, extracting and recognizing handwriting was very difficult. Matching handwriting is also very tough. Handwriting detection and signature detection in UiPath Document Understanding could be improved.

UiPath consistently improves their product based on user, customer, and community feedback. They are still enhancing capabilities for unstructured documents through GenAI implementation. They are doing their best to handle the variety of documents worldwide. Integration with UiPath Document Understanding, compared to the last two years, is now very easy and user-friendly.

I have been working with UiPath Document Understanding for three years.

For stability, UiPath Document Understanding rates an eight out of ten.

For scalability and ability to expand, UiPath Document Understanding deserves a ten out of ten.

As customers, we receive immediate support from the UiPath team. For technical support, they deserve a ten out of ten.

Positive

It takes time, but there are predefined templates available in the project. We can use these templates for document understanding, making the process quite straightforward and not too complicated.

We just need to grasp the concept, including labeling, digitization, extraction, and validation. Once we understand these components, using document understanding becomes very easy nowadays.

UiPath Document Understanding has helped clients reduce human errors. The bot processes approximately 300-400 documents per day, which would be difficult to review manually, making it very useful.

The cost is considerably high for UiPath Document Understanding.

Compared to other tools, UiPath Document Understanding performs quite well. Power Automate RPA tool is the main competitor. While there are multiple tools such as Automation Anywhere and Blue Prism, Power Automate is introducing new features relevant to document understanding and AI capabilities, making it a strong competitor for UiPath Document Understanding.

They have introduced Agentic AI in the agent builder and AI features such as Autopilot. This is very useful for speeding up development and delivering projects faster.

With Autopilot and Agentic AI, we can write prompts and build workflows. However, these workflows still need review, understanding, and possible modification. While AI integration has made development easier, there is a growing dependency on AI, which may lead to forgetting fundamental concepts and core knowledge.

I can recommend UiPath Document Understanding to other users. I would rate UiPath Document Understanding a seven out of ten.

The main use case for UiPath Document Understanding is to automatize delivery notes, foreign invoices, and nonstandard documents in general that do not have an electronic format but are PDF. Most of them are delivery notes, invoices, packing lists, or shipping documents.

We are working with all the solutions from the UiPath, such as UiPath Platform, Process Mining, Test Cloud, Document Understanding, and now we are starting to experiment with Agnetic AI.

We do use Forms AI because it's a part of the UiPath package. We have used this in some projects. We are experimenting with Agentic AI, and we are at the very beginning of the journey. The first project started but is not completed yet. 

The main benefits that UiPath Document Understanding provides include an increase in productivity, as it takes over tasks from humans, especially in Italy, where finding qualified people is challenging. It frees up resources to engage in value-added activities and enhances quality and compliance, particularly for projects with clients that have large patent portfolios.

UiPath Document Understanding helps reduce human error during the working process. For example, while reviewing results with the client, we noticed an invoice had the date of tomorrow, so human error is an issue for compliance and audit reasons.

Action Center is the most user-friendly tool I've seen in the market for validating the documents and extracted data.

The main area for improvement for UiPath Document Understanding is pricing. They are cutting out the middle market because 60,000 pages are very high for that segment. To have that, they have to pay for this package, which doesn't make sense for many clients.

For handwriting and signature understanding, the quality has to be quite good. It can read something standardized, such as the handwritten bank paper for bankruptcy, but when it comes to shipping notes, it has problems. The handwriting performance is not always good, which is understandable.

I have been working with UiPath Document Understanding for more or less four years.

For stability, I would rate UiPath Document Understanding a ten because I have never had any issues with it.

I would rate it an eight out of ten for scalability due to cost reasons, as it does have an impact, but from a technological point of view, it stands well.

As a golden partner of UiPath, their tech support is a ten out of ten for us. We are also a golden partner for Microsoft, and I would not rate that a ten.

Positive

The setup process for UiPath Document Understanding is simple.

The small bundle that UiPath sells for Document Understanding is 60,000 units or pages. Clients need to come close to 60,000 pages a year or more.

The main competitor for UiPath Document Understanding is Microsoft Azure with Power Automate. I prefer UiPath Document Understanding because Microsoft Power Automate lacks good connection capabilities to automate end-to-end processes. It's time-consuming and often results in lost data due to a lack of infrastructure control setup by the client. This is a known problem that Microsoft is likely addressing.

Overall, I would give UiPath Document Understanding a nine because, despite pricing being a pain point, the solution is really great and yields good results. 

We use Document Understanding to validate invoices during audits. The software reads the invoices in the first step of the process, and we process them before making the payment. You must review the process and validate what's in the invoice that goes into the Oracle ERP system. We cross-check to see if the value matches or not. 

We use Microsoft Forms to capture and extract the information, so we are executing lots of documents to Microsoft Form and auditing what's in the system, comparing that to the information in the invoices.

Document Understanding processes handwritten and printed documents in PDF, PNG, and Excel format, with a monthly volume of around 9,000. We have an 80 percent success rate of automated processing.  Only about 20 percent of documents require human validation. It takes about 30 minutes per document to validate by hand. 

Before automating, we had 14 people completing the process from end to end 8 hours a day. The bots reduce that to 2 people. Our success rate is 90 percent. On some days we've had a nearly 99 percent success rate. We're satisfied with the quality.

We are working with 40,000 different vendor templates. Document Understanding can understand and process various formats without much manual effort to configure the templates. That wasn't the case when we were using Microsoft. 

UiPath can read handwritten signatures with a success rate of around 70 percent. We've even processed pay slips in German. The language translations are around 90 percent accurate. 

The AI/ML component offers great flexibility in creating custom models. Its built-in models are also highly mature. The integration is seamless. We have RPA talking between our ERP systems and sharing information on the UiPath cloud.

I want more flexibility in Document Understanding's validation center.

I have used Document Understanding for 2 years.

I rate Document Understanding 10 out of 10 for stability. 

I rate Document Understanding seven out of 10 for scalability. 

I rate UiPath support 8 out of 10. 

Positive

We used previously used Microsoft Power Automate. We switched because we weren't satisfied with the outcome. Microsoft is more labor-intensive, and the data we were getting was less accurate.  We needed to put a lot of effort into configuring the templates each time the vendor sent us new templates. The success rate was only 30 to 40 percent. 

Document Understanding was easy to deploy, and it only took a day. It's deployed on one server on the East Coast, and only one department uses it. The solution requires about five or six hours of maintenance monthly.

I rate UiPath Document Understanding 2 out of 10 for affordability. It's one of the more expensive solutions on the market. 

I rate UiPath Document Understanding 8 out of 10. I recommend Document Understanding based on the quality of its results. It can read your handwritten documents and translate them. The outcome and success rate is higher than what I've seen in the traditional OCRs.

The primary use case for UiPath Document Understanding is to identify and classify documents, extract metadata, and use this data in automation workflows. This can be particularly useful in HR processes where various documents need to be submitted during hiring, such as graduation certificates, IDs, etc. UiPath Document Understanding helps classify these documents and extract the necessary data to process internally or initiate workflows.

UiPath Document Understanding is a tool that assists with processing documents containing various formats, including tables, handwritten text, and checkboxes.

We leverage machine learning and artificial intelligence to train UiPath Document Understanding on various documents. This integrated capability significantly simplifies extracting and comprehending information from these documents within the platform.

We can incorporate human validation into the training process to ensure accurate data classification and extraction. This valuable step, while adding a few minutes to the process, allows for human oversight and correction, ultimately improving the reliability and quality of the results.

UiPath Document Understanding helps reduce human errors, especially in data entry functions. 

By automating processes, UiPath Document Understanding can save approximately 70 percent of the time.

Customers realize value quickly with UiPath Document Understanding, typically seeing results within a few weeks of implementation.

UiPath Document Understanding offers valuable features like Arabic language support, which is crucial for effective communication and automation in the Arabic-speaking world. Furthermore, its integration with advanced language models leverages AI to quickly understand and classify document data, improving efficiency and accuracy in processing information.

One area where UiPath could improve is by including pre-trained models for general-use documents specific to the Middle East. This would enhance the platform's utility in the region by allowing users to more effectively automate tasks involving documents in Arabic and other Middle Eastern languages.

I have been using UiPath Document Understanding for almost five years.

The premium support UiPath offers is speedy and satisfactory. However, basic support may be somewhat limited.

Positive

For cloud deployment, the initial setup is fast and straightforward. On-premises setup, however, can be complicated and requires more effort.

Deploying UiPath Document Understanding in the cloud takes only a few minutes, while on-premises deployment requires three to five days.

UiPath Document Understanding is considered a bit expensive compared to other options like Microsoft Azure, which can offer similar quality at a more affordable rate.

I would rate UiPath Document Understanding seven out of ten.

Our old process involved manual data extraction from a large volume of documents with varying types and templates. This labor-intensive task required a significant workforce. We implemented UiPath Document Understanding to automate this process and eliminate the need for hand-coding solutions.

UiPath Document Understanding helps prepare data for machine learning by labeling documents used to train the models that will ultimately automate document processing tasks. We also use it to extract information from various identity documents like passports and ID cards, financial statements, credit card statements, and bank statements, and it can even process bank transaction data.

The documents we process using Document Understanding include tables and sometimes handwriting.

Around 70 percent of our documents are completely processed using Document Understanding.

The UiPath OCR works perfectly to extract handwriting, signatures, and multiple formats.

AI and machine learning prove valuable in training Document Understanding systems by analyzing data and identifying patterns, improving the system's ability to extract information from new documents.

AI streamlines Document Understanding by eliminating the need for manual coding. Users input documents into the AI, which then automatically classifies and extracts relevant information from each file. This saves staff over 20 hours a week.

UiPath Document Understanding integrates well with other systems.

For any newly implemented processes, human review will be necessary every day until Document Understanding is fully trained. The validation takes one minute per document.

The implementation of UiPath Document Understanding has saved us 50 percent of the time spent previously processing documents.

UiPath Document Understanding significantly reduces human error in processing documents, with complete accuracy achievable for standardized formats. However, its effectiveness in handling handwritten data varies depending on complexity.

UiPath Document Understanding helps save 20 percent of staff time to work on other tasks.                                          

The most valuable feature of UiPath Document Understanding is the AI Center.

UiPath Document Understanding, while effective for its own platform, could be even more valuable if it integrated with other commonly used platforms, allowing for a more universal approach to document processing.

I have been using UiPath Document Understanding for three years.

UiPath Document Understanding is stable.

UiPath Document Understanding is scalable.

The technical support is easy to access through the UiPath portal.

Positive

I've used IQ Bot from Automation Anywhere, Microsoft Intelligent Document Processing, and UiPath Document Understanding. IQ Bot and Document Understanding offer similar functionality, but only Microsoft's solution works across different platforms. We mainly use UiPath Document Understanding because it aligns with our client's preferred platform.

The deployment was straightforward. One person is enough for the deployment.

UiPath has a higher upfront cost, but its Document Understanding feature is not a significant additional expense compared to the overall platform.

I would rate UiPath Document Understanding nine out of ten.

We have six people that use UiPath Document Understanding.

I recommend UiPath Document Understanding to others.

We use the solution for purchase accounting, where we need a lot of invoices from various vendors.

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. The precision is not very high when there is a lot of text in the item table.

Sometimes, when the number of items is very large, the solution doesn't properly identify them. It's not 100% accurate, but it gives an 85% to 90% output. The solution doesn't work properly when too much data is on the table. Using 10 pages of data only for tables makes it difficult to collate the data.

We would like to have a better conversion of data, which is in tables and available on multiple pages. The same table is repeated with different items across multiple pages, which is challenging. We have to give similar keywords when indicating the second or third page. We should be able to use the same keyword for one document to identify the first page. From the second page onwards, the keyword should be done away with.

The repeated keywords on the second and third pages create problems because not many keywords are available on the second and third pages. It is a simple table-to-table repetition. The keywords, including the vendor's registration number, address, phone number, or email, are unavailable on the table pages.

Pages 2 to 10 are all just simple tables. The keywords are not available on those pages, and that's where the system gets more complicated.

I have been using UiPath Document Understanding for 3 years.

A person who knows the system can deploy it very easily and quickly without any difficulty or complication.

We take about 2 to 3 days to set up UiPath and install the UiPath Document Understanding programs we have developed. It takes time to create the vendor data and train the bot for each vendor. We spend about 40 minutes training the bot for each vendor.

The solution is a good investment. The investment of one year's license fees and development costs could be recovered in four to five months' time.

The product is not very costly in itself. It is part of the normal license. The solution’s cost increases for machine learning or artificial intelligence because we have to go for UiPath Orchestrator. UiPath Orchestrator's cost is very high, around $10,000 per year.

If somebody has a lot of vendors and about 100 invoices per day, we have to train the bot for various formats. We convert data from scanned PDF into a standard Excel table, including invoice numbers, purchasing order numbers, dates, and vendor names. The solution uses typed or printed data, not handwritten. It's difficult to capture handwritten data because different types of handwriting increase the errors in capturing the data.

About 80% of our organization’s documents are completely processed automatically. Sometimes, we don't have good data capture when the PDF is not of good quality. You need to have good-quality scans. Using the artificial intelligence or machine learning capabilities of UiPath Document Understanding is costly.

Integrating the solution with other ERP systems and applications is very easy. There are a lot of commands specifically for SAP. Initially, almost every document was verified by human beings. After gaining confidence and segregating the vendors who were giving out correct results, we stopped human intervention and started running on the bot completely.

When there were about 200 invoices per day, we employed about 5people to process the invoices manually in the ERP. When we introduced the UiPath Document Understanding bot, it could process faster and reduce the number of people required from 5 to 2. The solution helped reduce human errors and made processing in time possible, thereby avoiding delays.

Users should take the solution as an opportunity to reduce costs and not expect 100% results. Expecting 100% results would make it a failure from day 1 because it will not give 100% results. It will give you 80% accurate and 20% jumbled details because of the various complications arising from lengthy or unclear documents. If your expectation is reasonable, your success rate will be high.

Overall, I rate the solution an 8 out of 10.