UiPath Document Understanding
Using UiPath’s Document Understanding capabilities, PDFs or images can be read, classified, extracted into a readable format, and then uploaded to the AI Center to be validated. One of our Robotic Process Automation (RPA) experts walks through UiPath’s Document Understanding features, AI Center, and Validation Station.
This post was originally published on 7/29/2021
How can software bots understand and interpret documents from PDFs, handwritten notes, scans, and images? The solution: UiPath’s Document Understanding. Document Understanding is the UiPath product that enables bots to intelligently extract, interpret, and process data from many types of documents with the additional help of Artifical Intelligence(AI).
Document Understanding utilizes Robotic Process Automation, Optical Character Recognition (OCR), Machine Learning (ML), and AI to extract text from documents, analyze the text, and then provide the desired output.
UiPath’s Document Understanding provides a selection of different ML packages that may be utilized if you’ve been pretrained by UiPath, or you have the option to custom train the packages by utilizing AI Center.
Benefits of UiPath Document Understanding
Not only can documents be processed intelligently, but there are also more benefits Document Understanding provides:
How Does UiPath Document Understanding Work?
AI Center is a product that enables you to deploy, consume, manage, and improve machine learning models. This product allows you to choose which ML package you would like to use whether it be a custom-built package, pretrained, or trainable. For more information about AI Center, check out the UiPath documentation here.
In one of our recent projects here at Smartbridge, we utilized Document Understanding using the pretrained, publicly accessible endpoint for the “Invoices” ML package provided by UiPath. This Invoices package extracts relevant data from invoices such as invoice number, invoice date, due date, and total amount. Without any custom training to the package, we were able to completely automate about 30% of our invoice data to be extracted and input into an accounting system. The remaining 70% of invoices required some type of human interaction, such as selecting a missing field that was not extracted by using Validation Station.
Image of currently available UiPath Document Understanding Machine Learning Packages courtesy of UiPath
Validation Station is an activity in UiPath used when a document requires human validation. In the case of inaccuracies, low accuracy scores, or some exceptions, the software bot will send a notification to the person to either validate the data in the Validation Station or handle the exception in the Classification Station. This allows the user to review all of the extracted fields of the document that was processed in order to ensure its accuracy.
Within the UiPath Studio code, the process can be set up to send a document to Validation Station for any condition you want to define. Usually, this condition is when a required field is missing from the extraction, or the extraction is below a certain confidence level. This activity can be implemented with Action Center within UiPath Orchestrator to pause the processing of one invoice and continue with the remainder. Then once the invoice waiting in Action Center is validated, it will complete the rest of the job.
After custom training the provided UiPath Invoices machine learning package with our own training pipelines, we were able to fully automate about 70% of all invoices without any human interaction needed. For this number to improve over time, a developer must run more pipelines with new human validated invoice data as it comes through.
For more information on Validation Station, please refer to the UiPath documentation here.
Personally, I am very excited for every upcoming release, as they introduce further advancements in ML. Document Understanding and AI Center used in conjunction provide a truly robust autonomous process that learns and improves over time.
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