Abstract: Systems and methods for allocating computing environments for completing an RPA (robotic process automation) workload are provided. A request for completing an RPA workload is received. A number of computing environments to allocate for completing the RPA workload is calculated based on a selected one of a plurality of RPA autoscaling strategies. The calculated number of computing environments is allocated for allocating one or more RPA robots to complete the RPA workload. The computing environments may be virtual machines.

Abstract: Systems and methods for mapping interactive UI (user interface) elements to an RPA (robotic process automation) object repository are provided. User input selecting a window of an application displayed on a display device is received. In response to receiving the user input selecting the window of the application, interactive UI elements in the window of the application are automatically identified. User input selecting one or more of the identified interactive UI elements in the window of the application is received. The one or more selected interactive UI elements are stored in an RPA object repository of an RPA system.

Abstract: Systems and methods for mapping interactive UI (user interface) elements to an RPA (robotic process automation) object repository are provided. User input selecting a window of an application displayed on a display device is received. In response to receiving the user input selecting the window of the application, interactive UI elements in the window of the application are automatically identified. User input selecting one or more of the identified interactive UI elements in the window of the application is received. The one or more selected interactive UI elements are stored in an RPA object repository of an RPA system.

Abstract: Systems and methods for allocating computing environments for completing an RPA (robotic process automation) workload are provided. A request for completing an RPA workload is received. A number of computing environments to allocate for completing the RPA workload is calculated based on a selected one of a plurality of RPA autoscaling strategies. The calculated number of computing environments is allocated for allocating one or more RPA robots to complete the RPA workload. The computing environments may be virtual machines.

Abstract: An intelligent workflow design solution is provided that assists a user (e.g., developer of RPA workflows) by automatically and intelligently recommending suggested activities for use in building sequences of activities in an RPA workflow. The solution utilizes a predictive learning model to customize and personalize the workflow design process for a user, thereby shortening design cycle time and improving efficiency. A system and method for developing an RPA workflow includes monitoring one or more activities that are selected by a user and identifying one or more recommended activities as candidate next activities in a sequence based on a predictive learning model. The candidate next activities are generated for selection by the user and the predictive learning model is trained based on an actual selection by the user of a next activity for the sequence.