UiPath Task Mining - Preview

The UiPath Task Mining Guide - Preview


Step 2 appears twice in the overview section

UiPath Task Mining is an automation opportunity discovery tool. It collects employee desktop data comprising of the screenshot and log data upon each user action (mouse click, keystroke), then runs a machine learning model to analyze the data and suggest a list of processes with high automation potential.


  • Step 1: Admins create a project and invite users. Admins define the whitelisted applications for a project along with other customizable settings.
  • Step 2: Users install a recorder on the desktop to collect the screenshot and log data. We recommend that users record for 1-2 weeks to collect enough data for the analysis.
  • Step 3: A large amount of user action data is processed and analyzed by our proprietary machine learning model. The model looks for repetitive patterns among all the actions and identifies a list of repetitive processes that may be good automation candidates, along with the detailed metrics about each process (Total time spent, number of traces, apps used, etc.)
  • Step 4: Each identified automation candidate is presented in a graph showing the most frequent path and the variations, i.e., different ways in which employees execute the same process. A drill-down view is also possible for each trace, including a process replay.
  • Step 5: The process SMEs review the results, validate and select the processes to automate. The SMEs can one-click export any trace as a PDD file or a XAML file, which serves as a starting point for building automation at UiPath studio.

Use Cases

Task Mining allows customers to record the actions of selected users, analyze them together, and expose the results in various dashboards to:

  • Identify automation opportunities, the processes that have repeated frequently in the user action data
  • Understand the frequent path and variances for the candidate processes to possibly standardize and agree on the process before automating
  • Document the details of a candidate process to accelerate the development of automation

Benefit to All Stakeholders

  • RPA CoE leaders: efficiently discover automation opportunities and effectively engage the business teams by demonstrating an objective view of the opportunities - All at a fraction of the time and cost versus a traditional consulting-led approach
  • Business Analysts: avoid the time-consuming projects to interview or observe employees' work activities and then identify the repetitive processes with high automation potential. Easily view and analyze the detailed process metrics with the automation candidates. Reduce the time spent on documenting processes.
  • Employees: low touch process for the employees to set up and record. No impact on the day to day work. Preserves privacy by avoiding a human observer.
  • RPA developers: reduce the time spent on understanding the process before building automation.



Check out the Task Mining presentation page.

Updated 2 days ago


Step 2 appears twice in the overview section

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