The major use case I built using UiPath AI Center was for automated invoice extraction, where I created an ML model that extracts all the required fields from invoices. This helped me automate the process of invoice processing in SAP, and I used the default ML models provided by UiPath to train and fine-tune them according to my requirements. I trained approximately 1,000 documents in UiPath AI Center for this automation.Training and fine-tuning those ML models for invoice extraction was straightforward because UiPath AI Center provides a very good interface, allowing me to use it without needing deep technical knowledge. I simply upload some invoices and manually mark them using the provided markers; the interface is very friendly and easy to use, enabling any new person to quickly catch up with it. There was no significant learning curve involved. Regarding my main use case and my experience with document intelligence and invoice extraction automation, UiPath AI Center gives me everything I need. For instance, it also provides Action Center, from which I can train invoices with lower confidence. I set up a pipeline that retrains these low-confidence invoices automatically in UiPath AI Center, which has helped establish an automated pipeline process for training ML models without my intervention.
Team Lead at a tech services company with 51-200 employees
Real User
Top 5
Oct 31, 2025
UiPath AI Center is primarily used to build an ML model and train it based on invoices provided by vendors. Currently, work is being conducted with a medical firm that has insurance billable invoices, where the goal is to extract information based on business rules. Previously, work was completed for an insurance company where invoices were also processed in UiPath AI Center to extract information. UiPath AI Center solutions, specifically Document Understanding, are being used in the project, but not Autopilot.
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The major use case I built using UiPath AI Center was for automated invoice extraction, where I created an ML model that extracts all the required fields from invoices. This helped me automate the process of invoice processing in SAP, and I used the default ML models provided by UiPath to train and fine-tune them according to my requirements. I trained approximately 1,000 documents in UiPath AI Center for this automation.Training and fine-tuning those ML models for invoice extraction was straightforward because UiPath AI Center provides a very good interface, allowing me to use it without needing deep technical knowledge. I simply upload some invoices and manually mark them using the provided markers; the interface is very friendly and easy to use, enabling any new person to quickly catch up with it. There was no significant learning curve involved. Regarding my main use case and my experience with document intelligence and invoice extraction automation, UiPath AI Center gives me everything I need. For instance, it also provides Action Center, from which I can train invoices with lower confidence. I set up a pipeline that retrains these low-confidence invoices automatically in UiPath AI Center, which has helped establish an automated pipeline process for training ML models without my intervention.
UiPath AI Center is primarily used to build an ML model and train it based on invoices provided by vendors. Currently, work is being conducted with a medical firm that has insurance billable invoices, where the goal is to extract information based on business rules. Previously, work was completed for an insurance company where invoices were also processed in UiPath AI Center to extract information. UiPath AI Center solutions, specifically Document Understanding, are being used in the project, but not Autopilot.