UiPath Document Understanding 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.

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.

We use UiPath Document Understanding to comb through our documents, help us prepare reports, analyze the information, and later combine the information obtained into fact sheets, results, and reports that can be used for online planning and decision-making.

We implemented UiPath Document Understanding to build an accurate and intelligent platform. We needed a platform with the necessary tools to help us automate the whole process and reduce the errors involved in document Understanding, which arise from the manual processing of our documents.

We use UiPath Document Understanding for project management, which has also been implemented in customer service and production. So it's helping us in several business processes.

We have it deployed on the cloud and on-premise. We use the cloud for remote work, and it is used on-premises at the company workstation.

UiPath Document Understanding significantly streamlines our document-intensive processes through high accuracy, ensuring reliable and well-structured extracted information. It efficiently handles a wide range of documents, including both structured and unstructured PDFs.

UiPath Document Understanding helps us process structured and unstructured PDFs as well as handwritten, typed, and scanned documents.

We process 90 percent of our documents entirely through UiPath Document Understanding without requiring human intervention.

UiPath Document Understanding has significantly reduced the need for human involvement in document processing, allowing us to focus human resources on quality control. This automation has led to a time savings of approximately 60 percent.

UiPath Document Understanding does a good job handling various document formats, including handwritten and signature formats.

Machine learning capabilities are crucial and profitable because they significantly reduce the time spent on document data tasks and the number of errors encountered. As a result, machine learning is enhancing our productivity and enabling us to adapt to change more effectively.

Forms AI has proven reliable in predicting the content of packages within our documents, significantly reducing the number of errors in our product.

UiPath Document Understanding seamlessly integrates with various third-party platforms, allowing us to combine its capabilities with web analytics tools for enhanced data analysis and processing. Additionally, its easy integration with our CRM platform further optimizes our workflow.

UiPath Document Understanding has significantly benefited our organization by enabling remote work, reducing errors in document processing, and facilitating automation. We've eliminated the need for a large workforce dedicated to manual data entry, allowing us to operate efficiently with a smaller team. Additionally, the accurate data extracted through this technology empowers other departments to work seamlessly, transforming our organization into a well-oiled machine.

Initially, in an automation process, we have human validation every 48 hours, but now that UiPath Document Understanding has been so reliable, we can move to human validation every 72 hours.

The human validation takes three to four hours to complete.

UiPath Document Understanding has significantly reduced human error due to its accuracy.

Before implementing UiPath Document Understanding, processing ten documents took eight hours. Now, with UiPath Document Understanding, the same ten documents can be processed in less than thirty minutes.

The most beneficial aspects of UiPath Document Understanding for our data extraction needs have been the UiPath Academy courses and the free trial, which proved to be an eye-opener.

Machine learning has significantly benefited our organization by enabling the automation of numerous processes. We have successfully implemented machine learning to automate not only document generation but also report writing, analytics, and production. Furthermore, our CRM and planning processes have been streamlined through automation, which is made possible by machine learning. This technology has proven to be invaluable to our operations.

AI is helping us power robots and even expand our system capacity. It is the driving force behind remote working and also the driving force behind minimal human validation.

UiPath Document Understanding is a key tool we use to automate document processing for our clients, including tasks like invoice and sales order processing. We can create multiple workflows for different clients and even use it internally. To handle even more complex documents, we've also built custom models for specific data extraction needs.

UiPath Document Understanding helps our clients streamline data entry by accurately and consistently extracting information from both paper and digital documents. This extracted data can then be seamlessly integrated into their existing ERP or finance systems, eliminating the need for manual data input.

Document Understanding automates the processing of our invoices and sales orders, which are our most common tasks due to their semi-structured format. These documents share a typical organization with common fields, though we also handle custom documents like certificates and licenses across various states.

Document Understanding helps us process thousands of documents each day.

Thousands of documents are processed completely by Document Understanding each month.

Machine learning is the core of Document Understanding, where trained models extract data from documents. For simple forms, basic tools suffice. But in most cases, Document Understanding's built-in machine learning tackles complex documents. Generative AI features are new and basic for now but hold promise for the future.

The human validation required for Document Understanding outputs depends on the use case. We aim to get above 80 percent without human intervention. For some use cases, we're well above 90 percent. In just one minute, the human validation process can be completed for the small percentage of tasks, typically between 10 and 20 percent, that necessitate it.

While average handle time varied greatly before automation ranging from eight to ten minutes or even longer, data entry for sales orders with hundreds of line items was especially slow, taking up to 30 minutes per order. Automating the process with API integration significantly reduced this time to just one to two minutes.

Document Understanding helps significantly reduce human error, especially in crucial tasks like sales order entry for manufacturing clients. Mistyped entries can lead to incorrect production, rework, and unhappy customers. While the error reduction varies, estimates range from 18-20 percent to potentially as high as 40 percent in some cases.

Document Understanding significantly reduces manual data entry, freeing up staff time. For instance, one client eliminated a data entry role entirely, allowing that employee to focus on higher-value tasks. This is a consistent benefit – whenever we implement Document Understanding, the staff previously responsible for data entry can be redeployed to different teams, roles, or more strategic work.

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.

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.

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.                                          

We use UiPath Document Understanding to extract insurance document data related to vehicle accidents in a pilot project to better understand who is at fault. We open the documents, connect with the insurance companies, and obtain the police reports describing the scene of the accident. We extract the information into a single spreadsheet to charge the third party.

Before implementing UiPath Document Understanding, humans required around 15 minutes to extract the required information per document. Now, using Document Understanding, we can process 11 documents per minute with 98 percent accuracy, saving a significant amount of time and money.

The data we extract using Document Understanding relates to vehicle accidents. The insurance company uses this data to charge third parties involved and recover most of their money with minimal human intervention.

We are extracting information from 50 insurance documents to prove the concept of showing coverage for those involved in the accident.

The information from the insurance company is in PDF format and is structured so that we can easily extract information from it. The other public policy documents vary in quality depending on the state and district in Brazil. We have 27 states, and these documents are unstructured, making it difficult to extract data from them. Sometimes they are in image format, and other times they are in PDF format.

The 50 structured PDF documents from the insurance company are all 100 percent automated using UiPath Document Understanding.

We are impressed with the machine learning and AI capabilities of Document Understanding. We can use APIs to identify whenever a vehicle accident is reported, which helps our business.

Using the AI we can access vehicle accident reports and train the machine learning to understand the majority of the documents we extract information from to help improve our business processes.

We use the UiPath platform orchestrator with an API to integrate with OpenAI.

UiPath Document Understanding has helped our organization demonstrate to potential customers how the solution, together with AI and machine learning, can benefit their businesses.

Before Document Understanding our process took 15 minutes per document and now it takes under one minute.

Document Understanding has helped free up our staff's time to work on other projects.