UiPath, Inc. patent applications on January 9th, 2025
Patent Applications by UiPath, Inc. on January 9th, 2025
UiPath, Inc.: 2 patent applications
UiPath, Inc. has applied for patents in the areas of G06N20/00 (2), G06F8/36 (1), G06F8/34 (1) G06F8/36 (1), G06N20/00 (1)
With keywords such as: workflow, rpa, trained, stored, sequences, time, user, recommendations, activities, and predict in patent application abstracts.
Patent Applications by UiPath, Inc.
Inventor(s): Kartik IYER of Karnataka (IN) for uipath, inc., Radhakrishnan IYER of Karnataka (IN) for uipath, inc., Naveen KUMAR M of Karnataka (IN) for uipath, inc.
IPC Code(s): G06F8/36, G06F8/34, G06N20/00
CPC Code(s): G06F8/36
Abstract: training and using artificial intelligence (ai)/machine learning (ml) models to automatically supplement and/or complete code of rpa workflows is disclosed. a trained ai/ml model may intelligently and automatically predict and complete the next series of activities in rpa workflows (e.g., one, a few, many, the remainder of the workflow, etc.). actions users take while creating workflows over a time period may be captured and stored. the ai/ml model may then be trained and used to match the stored actions with stored workflow sequences of actions in order to predict and complete the workflow. as more and more workflow sequences are captured and stored over time, the ai/ml model may be retrained to predict a larger number of sequences and/or to more accurately make predictions. auto-completion may occur in real-time in some embodiments to save time and effort by the user.
Inventor(s): Mircea Grigore of Bucharest (RO) for uipath, inc.
IPC Code(s): G06N20/00
CPC Code(s): G06N20/00
Abstract: an artificial intelligence (ai)/machine learning (ml) recommendation engine for robotic process automation (rpa) is disclosed. an ai/ml model may be trained to provide recommendations for a next activity, a next sequence of activities, and/or modifications to parameters for one or more existing activities to include during rpa workflow development. the recommendations may be based on the context of where the user is in the rpa workflow. for user interface (ui) automations, the ai/ml model may be linked to an object repository and trained to make recommendations therefrom. the ai/ml model may also be trained to generate new ui descriptors for the object repository.