Patents by Inventor Prabhdeep Singh

Prabhdeep Singh has filed for patents to protect the following inventions. This listing includes patent applications that are pending as well as patents that have already been granted by the United States Patent and Trademark Office (USPTO).

  • Patent number: 12353455
    Abstract: Various embodiments of a Title Engine generate search results that identify content available in a content corpus in response to receiving a search query for content that is currently unavailable in the content corpus. Rather than returning output merely indicating absence of the requested content set forth in the received search query, the Title Engine identifies various content available in the content corpus that is similar to the search query's requested—but unavailable—content. The Title Engine identifies content in a content corpus that is similar to requested content that has been determined as unavailable. Upon determining unavailability of the requested particular content in the content corpus, the Title Engine generates a pseudo-identifier for the requested particular content. The Title Engine inserts the pseudo-identifier into a sequence of content identifiers. The Title Engine generates an embedding for the pseudo-identifier.
    Type: Grant
    Filed: March 29, 2024
    Date of Patent: July 8, 2025
    Assignee: Scribd, Inc.
    Inventors: Matthew Allen Strong Ross, Azadeh Haji Hosseini, Monique Alves Cruz, Albert Jimenez Sanfiz, Prabhdeep Singh Cheema, Hima Kiran Alladi
  • Patent number: 12337464
    Abstract: Artificial intelligence (AI)-based process identification, extraction, and automation for robotic process automation (RPA) is disclosed. Listeners may be deployed to user computing systems to collect data pertaining to user actions. The data collected by the listeners may then be sent to one or more servers and be stored in a database. This data may be analyzed by AI layers to recognize patterns of user behavioral processes therein. These recognized processes may then be distilled into respective RPA workflows and deployed to automate the processes.
    Type: Grant
    Filed: May 15, 2023
    Date of Patent: June 24, 2025
    Assignee: UiPath, Inc.
    Inventors: Prabhdeep Singh, Christian Berg
  • Publication number: 20250189951
    Abstract: Human-in-the-loop robot training using artificial intelligence (AI) for robotic process automation (RPA) is disclosed. This may be accomplished by a listener robot watching interactions of a user or another robot with a computing system. Based on the interactions by the user or robot with the computing system, the robot may be improved and/or personalized for the user or a group of users.
    Type: Application
    Filed: November 16, 2023
    Publication date: June 12, 2025
    Applicant: UiPath, Inc.
    Inventors: Prabhdeep SINGH, Liji KUNNATH, Palak KADAKIA
  • Patent number: 12321876
    Abstract: Artificial intelligence (AI)/machine learning (ML) model drift detection and correction for robotic process automation (RPA) is disclosed. Information is analyzed pertaining to input data for an AI/ML model to determine whether data drift has occurred, analyze information pertaining to results from execution of the AI/ML model to determine whether model drift has occurred, or both. When, based on the analysis of the information, a change condition is found, a change threshold is met or exceeded, or both, the AI/ML model is retrained. The retrained AI/ML model may then be deployed to provide better predictions on real world data.
    Type: Grant
    Filed: July 21, 2020
    Date of Patent: June 3, 2025
    Assignee: UiPath, Inc.
    Inventors: Prabhdeep Singh, Anton McGonnell, Marco Alban Hidalgo
  • Patent number: 12321823
    Abstract: A machine learning (ML) model retraining pipeline for robotic process automation (RPA) is disclosed. When an ML model is deployed in a production or development environment, RPA robots send requests to the ML model when executing their workflows. When a confidence level of the ML model falls below a certain confidence, training data is collected, potentially from a large number of computing systems. The ML model is then trained using at least in part the collected training data, and a new version of the ML model is deployed.
    Type: Grant
    Filed: April 30, 2020
    Date of Patent: June 3, 2025
    Assignee: UiPath, Inc.
    Inventors: Prabhdeep Singh, Marco Alban Hidalgo, Anton McGonnell
  • Patent number: 12263593
    Abstract: Process evolution for robotic process automation (RPA) and RPA workflow micro-optimization are disclosed. Initially, an RPA implementation may be scientifically planned, potentially using artificial intelligence (AI). Embedded analytics may be used to measure, report, and align RPA operations with strategic business outcomes. RPA may then be implemented by deploying AI skills (e.g., in the form of machine learning (ML) models) through an AI fabric that seamlessly applies, scales, manages AI for RPA workflows of robots. This cycle of planning, measuring, and reporting may be repeated, potentially guided by more and more AI, to iteratively improve the effectiveness of RPA for a business. RPA implementations may also be identified and implemented based on their estimated return on investment (ROI).
    Type: Grant
    Filed: March 4, 2024
    Date of Patent: April 1, 2025
    Assignee: UiPath, Inc.
    Inventors: Prabhdeep Singh, Christian Berg
  • Patent number: 12153400
    Abstract: Human-in-the-loop robot training using artificial intelligence (AI) for robotic process automation (RPA) is disclosed. This may be accomplished by a listener robot watching interactions of a user or another robot with a computing system. Based on the interactions by the user or robot with the computing system, the robot may be improved and/or personalized for the user or a group of users.
    Type: Grant
    Filed: December 9, 2019
    Date of Patent: November 26, 2024
    Assignee: UiPath, Inc.
    Inventors: Prabhdeep Singh, Liji Kunnath, Palak Kadakia
  • Patent number: 12147898
    Abstract: Artificial intelligence (AI) layer-based process extraction for robotic process automation (RPA) is disclosed. Data collected by RPA robots and/or other sources may be analyzed to identify patterns that can be used to suggest or automatically generate RPA workflows. These AI layers may be used to recognize patterns of user or business system processes contained therein. Each AI layer may “sense” different characteristics in the data and be used individually or in concert with other AI layers to suggest RPA workflows.
    Type: Grant
    Filed: December 4, 2023
    Date of Patent: November 19, 2024
    Assignee: UiPath, Inc.
    Inventors: Prabhdeep Singh, Christian Berg
  • Publication number: 20240296179
    Abstract: Various embodiments of a Title Engine generate search results that identify content available in a content corpus in response to receiving a search query for content that is currently unavailable in the content corpus. Rather than returning output merely indicating absence of the requested content set forth in the received search query, the Title Engine identifies various content available in the content corpus that is similar to the search query's requested—but unavailable—content. The Title Engine identifies content in a content corpus that is similar to requested content that has been determined as unavailable. Upon determining unavailability of the requested particular content in the content corpus, the Title Engine generates a pseudo-identifier for the requested particular content. The Title Engine inserts the pseudo-identifier into a sequence of content identifiers. The Title Engine generates an embedding for the pseudo-identifier.
    Type: Application
    Filed: March 29, 2024
    Publication date: September 5, 2024
    Inventors: Matthew Allen Strong Ross, Azadeh Haji Hosseini, Monique Alves Cruz, Albert Jimenez Sanfiz, Prabhdeep Singh Cheema, Hima Kiran Alladi
  • Publication number: 20240208049
    Abstract: Process evolution for robotic process automation (RPA) and RPA workflow micro-optimization are disclosed. Initially, an RPA implementation may be scientifically planned, potentially using artificial intelligence (AI). Embedded analytics may be used to measure, report, and align RPA operations with strategic business outcomes. RPA may then be implemented by deploying AI skills (e.g., in the form of machine learning (ML) models) through an AI fabric that seamlessly applies, scales, manages AI for RPA workflows of robots. This cycle of planning, measuring, and reporting may be repeated, potentially guided by more and more AI, to iteratively improve the effectiveness of RPA for a business. RPA implementations may also be identified and implemented based on their estimated return on investment (ROI).
    Type: Application
    Filed: March 4, 2024
    Publication date: June 27, 2024
    Applicant: UiPath, Inc.
    Inventors: Prabhdeep Singh, Christian Berg
  • Publication number: 20240103496
    Abstract: Human-in-the-loop robot training using artificial intelligence (AI) for robotic process automation (RPA) is disclosed. This may be accomplished by a listener robot watching interactions of a user or another robot with a computing system. Based on the interactions by the user or robot with the computing system, the robot may be improved and/or personalized for the user or a group of users.
    Type: Application
    Filed: November 16, 2023
    Publication date: March 28, 2024
    Applicant: UiPath, Inc.
    Inventors: Prabhdeep SINGH, Liji KUNNATH, Palak KADAKIA
  • Publication number: 20240104381
    Abstract: Artificial intelligence (AI) layer-based process extraction for robotic process automation (RPA) is disclosed. Data collected by RPA robots and/or other sources may be analyzed to identify patterns that can be used to suggest or automatically generate RPA workflows. These AI layers may be used to recognize patterns of user or business system processes contained therein. Each AI layer may “sense” different characteristics in the data and be used individually or in concert with other AI layers to suggest RPA workflows.
    Type: Application
    Filed: December 4, 2023
    Publication date: March 28, 2024
    Applicant: UiPath, Inc.
    Inventors: Prabhdeep SINGH, Christian BERG
  • Patent number: 11919165
    Abstract: Process evolution for robotic process automation (RPA) and RPA workflow micro-optimization are disclosed. Initially, an RPA implementation may be scientifically planned, potentially using artificial intelligence (AI). Embedded analytics may be used to measure, report, and align RPA operations with strategic business outcomes. RPA may then be implemented by deploying AI skills (e.g., in the form of machine learning (ML) models) through an AI fabric that seamlessly applies, scales, manages AI for RPA workflows of robots. This cycle of planning, measuring, and reporting may be repeated, potentially guided by more and more AI, to iteratively improve the effectiveness of RPA for a business. RPA implementations may also be identified and implemented based on their estimated return on investment (ROI).
    Type: Grant
    Filed: February 6, 2023
    Date of Patent: March 5, 2024
    Assignee: UiPath, Inc.
    Inventors: Prabhdeep Singh, Christian Berg
  • Publication number: 20240061760
    Abstract: Probabilistic models may be used in a deterministic workflow for robotic process automation (RPA). Machine learning (ML) introduces a probabilistic framework where the outcome is not deterministic, and therefore, the steps are not deterministic. Deterministic workflows may be mixed with probabilistic workflows, or probabilistic activities may be inserted into deterministic workflows, in order to create more dynamic workflows. A supervisor system may be used to monitor an ML model and raise an alarm, disable an RPA robot, bypass an RPA robot, or roll back to a previous version of the ML model when an error is detected by a data drift detector, a concept drift detector, or both.
    Type: Application
    Filed: October 30, 2023
    Publication date: February 22, 2024
    Applicant: UiPath, Inc.
    Inventors: Prabhdeep Singh, Anton McGonnell
  • Patent number: 11893371
    Abstract: Using artificial intelligence (AI) to select and/or chain robotic process automation (RPA) models a given problem is disclosed. A model of models (e.g., an RPA robot or an ML model) may serve as an additional layer on an existing system that makes the existing models more effective. This model of models may incorporate AI that learns an improved or best set of rules or an order from existing models, potentially taking certain activities from a model, feeding input from one model into another, and/or chaining models in some embodiments.
    Type: Grant
    Filed: March 12, 2021
    Date of Patent: February 6, 2024
    Assignee: UiPath, Inc.
    Inventor: Prabhdeep Singh
  • Publication number: 20230393870
    Abstract: Use of generative artificial intelligence (AI)/machine learning (ML) models is disclosed to determine sequences of user interactions with computing systems, extract common processes, and generate robotic process automation (RPA) robots. The generative AI/ML model may be trained to recognize matching n-grams of user interactions and/or a beneficial end state. Recorded real user interactions may be analyzed, and matching sequences may be implemented as corresponding activities in an RPA workflow.
    Type: Application
    Filed: August 11, 2023
    Publication date: December 7, 2023
    Applicant: UiPath, Inc.
    Inventor: Prabhdeep Singh
  • Patent number: 11836626
    Abstract: Artificial intelligence (AI) layer-based process extraction for robotic process automation (RPA) is disclosed. Data collected by RPA robots and/or other sources may be analyzed to identify patterns that can be used to suggest or automatically generate RPA workflows. These AI layers may be used to recognize patterns of user or business system processes contained therein. Each AI layer may “sense” different characteristics in the data and be used individually or in concert with other AI layers to suggest RPA workflows.
    Type: Grant
    Filed: November 1, 2022
    Date of Patent: December 5, 2023
    Assignee: UiPath, Inc.
    Inventors: Prabhdeep Singh, Christian Berg
  • Publication number: 20230385085
    Abstract: Use of generative artificial intelligence (AI)/machine learning (ML) models is disclosed to determine sequences of user interactions with computing systems, extract common processes, and generate robotic process automation (RPA) robots. The generative AI/ML model may be trained to recognize matching n-grams of user interactions and/or a beneficial end state. Recorded real user interactions may be analyzed, and matching sequences may be implemented as corresponding activities in an RPA workflow.
    Type: Application
    Filed: August 10, 2023
    Publication date: November 30, 2023
    Applicant: UiPath, Inc.
    Inventor: Prabhdeep Singh
  • Patent number: 11815880
    Abstract: Human-in-the-loop robot training using artificial intelligence (AI) for robotic process automation (RPA) is disclosed. This may be accomplished by a listener robot watching interactions of a user or another robot with a computing system. Based on the interactions by the user or robot with the computing system, the robot may be improved and/or personalized for the user or a group of users.
    Type: Grant
    Filed: October 20, 2021
    Date of Patent: November 14, 2023
    Assignee: UiPath, Inc.
    Inventors: Prabhdeep Singh, Liji Kunnath, Palak Kadakia
  • Publication number: 20230360388
    Abstract: Techniques for training a generative artificial intelligence (AI) / machine learning (ML) model to recognize applications, screens, and UI elements using computer vision (CV) and to recognize user interactions with the applications, screens, and UI elements are disclosed. Optical character recognition (OCR) may also be used to assist in training the generative AI/ML model. Training of the generative AI/ML model may be performed without other system inputs such as system-level information (e.g., key presses, mouse clicks, locations, operating system operations, etc.) or application-level information (e.g., information from an application programming interface (API) from a software application executing on a computing system), or the training of the generative AI/ML model may be supplemented by other information, such as browser history, heat maps, file information, currently running applications and locations, system level and/or application-level information, etc.
    Type: Application
    Filed: July 20, 2023
    Publication date: November 9, 2023
    Applicant: UiPath, Inc.
    Inventor: Prabhdeep SINGH