UiPath had 12 patents in robotics during Q1 2024. UiPath Inc’s patents in Q1 2024 focus on enhancing robotic process automation (RPA) through artificial intelligence (AI) layers for process extraction, human-in-the-loop robot training, pre-authorized access control, integration of probabilistic models in deterministic workflows, and executing digital assistant tasks using RPA. These innovations aim to improve RPA efficiency, personalization, and dynamic workflow creation by leveraging AI, machine learning, and user-friendly interfaces. GlobalData’s report on UiPath gives a 360-degree view of the company including its patenting strategy. Buy the report here.

UiPath grant share with robotics as a theme is 50% in Q1 2024. Grant share is based on the ratio of number of grants to total number of patents.

Recent Patents

Application: Artificial intelligence layer-based process extraction for robotic process automation (Patent ID: US20240104381A1)

The patent filed by UiPath Inc. describes a computer-implemented method for AI-based process extraction for robotic process automation (RPA). The method involves running data through AI models to identify RPA processes that exceed a confidence threshold and generating RPA workflows based on the identified processes. The AI models may include various layers such as sequence extraction, clustering detection, visual component detection, text recognition, and audio-to-text translation, which work collectively to suggest RPA workflows. Additionally, the method includes generating automations for RPA robots to implement the generated workflows and replacing existing RPA processes with more optimal ones identified through the AI models.

Furthermore, the patent also covers the use of non-transitory computer-readable media storing computer programs that run data through AI models to identify RPA processes exceeding a confidence threshold and generate corresponding RPA workflows. The programs may also facilitate the generation of automations for executing the workflows and replacing less optimal existing RPA processes with the identified ones. The patent emphasizes the use of a combination of AI models, run either in series, parallel, or a combination of both, to effectively process data and improve RPA processes. Overall, the invention aims to enhance RPA efficiency by leveraging AI-based process extraction to identify, suggest, and automate workflows for improved business processes.

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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.