What needs improvement with UiPath Document Understanding?

UiPath Document Understanding's training can be improved to focus more on how to handle the robots. Extending the trial period for UiPath Document Understanding from three to six months would allow organizations to evaluate their capabilities thoroughly.

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.

The rising annual licensing cost of UiPath's Document Understanding product is a major turnoff for users. This constant price fluctuation incentivizes companies to switch to competing solutions, potentially hurting UiPath's market competitiveness. The technical support has significant room for improvement.

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.

UiPath Document Understanding has challenges with handwriting and screenshots.

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

Document Understanding's handwriting comprehension is improving, but it's still not as good as printed documents. Machine learning models, in general, are becoming mature, but it's still not to a point where I will give it five stars. I may give it a two or three. It is still not advanced enough to identify whatever handwritten content you give to it. It can process handwriting, but you need a human to validate it. With more training, it will become more automated. It will be better by 2025, but it is still not mature enough Similarly, there is still room for improvement in reading printed documents. Ideally, if you have a model, Document Understanding should be able to extract every field from there. That's what customers expect.

The extraction can be better. ABBYY FlexiCapture has more capabilities than Document Understanding. It can also extract automatically without training, whereas with Document Understanding, we need to train everything. For example, we have uploaded ten invoices of a type, and when we upload the eleventh invoice, it can find approximately eight fields out of ten, but ABBYY FlexiCapture can find ten out of ten. More documents are required to train Document Understanding. There should be Generative AI and sentiment analysis. These two things will be very good.

At the end of the process, we classify documents in our external application, similar to a CRM system. This classification is based on the documents stored in the new system. The results of classifying patient documents within UiPath Document Understanding need to be more accurate.

UiPath Document Understanding requires more database connectors. I encountered difficulty connecting to Workbench from MySQL, necessitating a workaround.

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.

I wish to have more pre-trained modules available in various languages. For instance, while Document Understanding currently supports Hebrew for Israel, I would appreciate the addition of pre-trained modules specifically tailored for different Hebrew-related forms. This enhancement could prove to be quite beneficial.

Its pricing can be improved.

It would be much easier if UiPath increased the count of pages. Currently, they are allowing one million pages for $10,000 per month. I would prefer to increase the page count or reduce the dollar count in terms of processing the documents. I would prefer $6,000 per month for processing 2 to 3 million pages per month. It will then be much easier for companies with a low budget to use this product.

There is room for improvement in handwriting processes. It should enhance the user interface for constructing extraction logic. It is not as user-friendly as other parts of the platform. An additional feature that could be considered is the integration with generative AI. The deployment process should be more user-friendly and streamlined. Scalability capabilities should be improved, as well.

Several areas require improvement in UiPath. The licensing model poses a significant challenge due to the fee charged for posting a model, which impedes the development of productivity-enhancing models. Additionally, UiPath's pricing is substantially higher than that of its competitors, approximately three to four times higher. UiPath's AI quality needs substantial improvement. Several issues have persisted for at least two years, such as the inability to handle breaks in tables. When data in a table extends from the first page to the second, UiPath fails to process it effectively. Additionally, UiPath struggles to handle multiple items.

Over the past few years, I have observed that the invoice model consistently improves with each new UiPath release. There is still room for enhancement in capturing line items from invoices. This is one of the areas where I believe we can achieve near-perfect data capture. Unfortunately, the current accuracy rate for capturing line items is between 50 and 60 percent. This necessitates manual two-way matching, which is time-consuming and inefficient. I believe UiPath Document Understanding can still improve in this area, but overall, it is moving in the right direction. Despite advancements in artificial intelligence and machine learning, there are lingering concerns about data privacy and security. These concerns can have a significant impact on users, particularly in terms of geographic restrictions and data policies. The accuracy level we receive does not justify the price, as many competitors are offering much lower prices.

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.

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.

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.

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.

Sometimes we have challenges when we need to read something like a barcode, so we must use the Cisco algorithm to solve the issue, or I have to ask developers for help specifically to capture this kind of information. There are other processes, such as refunds, that we still must do manually because there is no way to use automation to solve this issue.

One area of improvement for UiPath Document Understanding is the accuracy of handwritten documents. While the solution supports handwritten documents, the accuracy percentage is not as high as desired. Therefore, it would be preferable if UiPath could focus on improving the accuracy of handwritten documents in their next release. Although they currently support handwritten documents, the accuracy is still low. Also, the documents for the solution are lengthy, and because of this, I say that the solution should incorporate some video sessions.

Document Understanding would be improved with more AI platforms. Its localization and OCR could also be better. In the next release, Document Understanding should include custom and pre-defined reporting.

Currently, we have to train multiple templates because the column size and row size change in each PDF. My solution is to improve the process by training only one particular template so that the information can be extracted regardless of the row size and column size variations in the PDF. This way, we won't need to train each and every template.

The solution is quite expensive.