UiPath has been granted a patent for systems and methods that allocate computing environments for completing RPA workloads. The technology involves receiving requests, calculating the number of computing environments needed based on autoscaling strategies, and allocating resources for RPA robots to complete tasks efficiently. GlobalData’s report on UiPath gives a 360-degree view of the company including its patenting strategy. Buy the report here.

According to GlobalData’s company profile on UiPath, AI for workflow management was a key innovation area identified from patents. UiPath's grant share as of April 2024 was 26%. Grant share is based on the ratio of number of grants to total number of patents.

Dynamic allocation of computing environments for rpa workload completion

Source: United States Patent and Trademark Office (USPTO). Credit: UiPath Inc

A recently granted patent (Publication Number: US11971705B2) discloses a computer-implemented method for managing Robotic Process Automation (RPA) workloads efficiently. The method involves receiving a request for completing an RPA workload, determining the number of computing environments needed based on selected RPA autoscaling strategies, and allocating these environments to RPA robots for workload completion. The patent outlines various RPA autoscaling strategies, including dynamic, speed over cost, balanced, and cost over speed strategies, allowing for flexible and optimized resource allocation.

Furthermore, the patent describes the customization options available to users, such as configuring control variables for a custom autoscaling strategy. The method also includes features like user selection of autoscaling strategies, automatic strategy selection based on predefined schedules or workload sources, and the use of virtual machines as computing environments. The patent covers not only the computer-implemented method but also an apparatus and a non-transitory computer-readable medium storing program instructions for implementing the described operations. Overall, the patent aims to enhance the efficiency and scalability of RPA workloads by intelligently managing computing resources based on workload demands and user preferences.

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GlobalData Patent Analytics tracks bibliographic data, legal events data, point in time patent ownerships, and backward and forward citations from global patenting offices. Textual analysis and official patent classifications are used to group patents into key thematic areas and link them to specific companies across the world’s largest industries.