Patents by Inventor Gregory Klose

Gregory Klose 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).

  • Customer journey management engine
    Patent number: 11783375
    Abstract: Provided is a process, including: obtaining a first training dataset, training a first machine-learning model on the first training dataset, obtaining a set of candidate question sequences, forming virtual subject-entity records, forming a second training dataset, training a second machine-learning model, and storing the adjusted parameters of the second machine-learning model in memory.
    Type: Grant
    Filed: July 8, 2022
    Date of Patent: October 10, 2023
    Assignee: Cerebri AI Inc.
    Inventors: Alain Charles Briancon, Jean Joseph Belanger, James Cvetan Stojanov, Christopher Michael Coovrey, Pranav Mahesh Makhijani, Gregory Klose, Max Changchun Huang, Mounib Mohamad Ismail, Michael Henry Engeling, Hongshi Li
  • MACHINE-LEARNING MODELS TO LEVERAGE BEHAVIOR-DEPENDENT PROCESSES
    Publication number: 20230186083
    Abstract: Provided is a process, including: obtaining a first training dataset of subject-entity records; training a first machine-learning model on the first training dataset; forming virtual subject-entity records by appending members of a set of candidate action sequences to time-series of at least some of the subject-entity records; forming a second training dataset by labeling the virtual subject-entity records with predictions of the first machine-learning model; and training a second machine-learning model on the second training dataset.
    Type: Application
    Filed: November 15, 2022
    Publication date: June 15, 2023
    Inventors: Gabriel M. Silberman, Alain Briancon, Gregory Klose, Michael Wegan, Lee Harper, Andrew Kraemer, Arun Prakash
  • CUSTOMER JOURNEY MANAGEMENT ENGINE
    Publication number: 20230101487
    Abstract: Provided is a process, including: obtaining a first training dataset, training a first machine-learning model on the first training dataset, obtaining a set of candidate question sequences, forming virtual subject-entity records, forming a second training dataset, training a second machine-learning model, and storing the adjusted parameters of the second machine-learning model in memory.
    Type: Application
    Filed: July 8, 2022
    Publication date: March 30, 2023
    Inventors: Alain Charles Briancon, Jean Joseph Belanger, James Cvetan Stojanov, Christopher Michael Coovrey, Pranav Mahesh Makhijani, Gregory Klose, Max Changchun Huang, Mounib Mohamad Ismail, Michael Henry Engeling, Hongshi Li
  • Machine-learning models to leverage behavior-dependent processes
    Patent number: 11537878
    Abstract: Provided is a process, including: obtaining a first training dataset of subject-entity records; training a first machine-learning model on the first training dataset; forming virtual subject-entity records by appending members of a set of candidate action sequences to time-series of at least some of the subject-entity records; forming a second training dataset by labeling the virtual subject-entity records with predictions of the first machine-learning model; and training a second machine-learning model on the second training dataset.
    Type: Grant
    Filed: May 9, 2019
    Date of Patent: December 27, 2022
    Assignee: Cerebri AI Inc.
    Inventors: Gabriel M. Silberman, Alain Briançon, Gregory Klose, Michael Wegan, Lee Harper, Andrew Kraemer, Arun Prakash
  • Customer journey management engine
    Patent number: 11416896
    Abstract: Provided is a process, including: obtaining a first training dataset, training a first machine-learning model on the first training dataset, obtaining a set of candidate question sequences, forming virtual subject-entity records, forming a second training dataset, training a second machine-learning model, and storing the adjusted parameters of the second machine-learning model in memory.
    Type: Grant
    Filed: June 18, 2021
    Date of Patent: August 16, 2022
    Assignee: Cerebri AI Inc.
    Inventors: Alain Charles Briancon, Jean Joseph Belanger, James Cvetan Stojanov, Christopher Michael Coovrey, Pranav Mahesh Makhijani, Gregory Klose, Max Changchun Huang, Mounib Mohamad Ismail, Michael Henry Engeling, Hongshi Li
  • CUSTOMER JOURNEY MANAGEMENT ENGINE
    Publication number: 20220044283
    Abstract: Provided is a process, including: obtaining a first training dataset, training a first machine-learning model on the first training dataset, obtaining a set of candidate question sequences, forming virtual subject-entity records, forming a second training dataset, training a second machine-learning model, and storing the adjusted parameters of the second machine-learning model in memory.
    Type: Application
    Filed: June 18, 2021
    Publication date: February 10, 2022
    Inventors: Alain Charles Briancon, Jean Joseph Belanger, James Cvetan Stojanov, Christopher Michael Coovrey, Pranav Mahesh Makhijani, Gregory Klose, Max Changchun Huang, Mounib Mohamad Ismail, Michael Henry Engeling, Hongshi Li
  • Customer journey management engine
    Patent number: 11068942
    Abstract: Provided is a process, including: obtaining a first training dataset, training a first machine-learning model on the first training dataset, obtaining a set of candidate question sequences, forming virtual subject-entity records, forming a second training dataset, training a second machine-learning model, and storing the adjusted parameters of the second machine-learning model in memory.
    Type: Grant
    Filed: October 18, 2019
    Date of Patent: July 20, 2021
    Assignee: Cerebri AI Inc.
    Inventors: Alain Charles Briancon, Jean Joseph Belanger, James Cvetan Stojanov, Christopher Michael Coovrey, Pranav Mahesh Makhijani, Gregory Klose, Max Changchun Huang, Mounib Mohamad Ismail, Michael Henry Engeling, Hongshi Li
  • CUSTOMER JOURNEY MANAGEMENT ENGINE
    Publication number: 20200126126
    Abstract: Provided is a process, including: obtaining a first training dataset, training a first machine-learning model on the first training dataset, obtaining a set of candidate question sequences, forming virtual subject-entity records, forming a second training dataset, training a second machine-learning model, and storing the adjusted parameters of the second machine-learning model in memory.
    Type: Application
    Filed: October 18, 2019
    Publication date: April 23, 2020
    Inventors: Alain Charles Briancon, Jean Joseph Belanger, James Cvetan Stojanov, Christopher Michael Coovrey, Pranav Mahesh Makhijani, Gregory Klose, Max Changchun Huang, Mounib Mohamad Ismail, Michael Henry Engeling, Hongshi Li
  • MULTI-STAGE MACHINE-LEARNING MODELS TO CONTROL PATH-DEPENDENT PROCESSES
    Publication number: 20200082261
    Abstract: Provided is a process, including: obtaining a first training dataset of subject-entity records; training a first machine-learning model on the first training dataset; forming virtual subject-entity records by appending members of a set of candidate action sequences to time-series of at least some of the subject-entity records; forming a second training dataset by labeling the virtual subject-entity records with predictions of the first machine-learning model; and training a second machine-learning model on the second training dataset.
    Type: Application
    Filed: May 9, 2019
    Publication date: March 12, 2020
    Inventors: Gabriel M. Silberman, Alain Briançon, Gregory Klose, Michael Wegan, Lee Harper, Andrew Kraemer, Arun Prakash
  • Multi-stage machine-learning models to control path-dependent processes
    Patent number: 10402723
    Abstract: Provided is a process, including: obtaining a first training dataset of subject-entity records; training a first machine-learning model on the first training dataset; forming virtual subject-entity records by appending members of a set of candidate action sequences to time-series of at least some of the subject-entity records; forming a second training dataset by labeling the virtual subject-entity records with predictions of the first machine-learning model; and training a second machine-learning model on the second training dataset.
    Type: Grant
    Filed: September 11, 2018
    Date of Patent: September 3, 2019
    Assignee: Cerebri AI Inc.
    Inventors: Gabriel M. Silberman, Alain Briançon, Gregory Klose, Michael Wegan, Lee Harper, Andrew Kraemer, Arun Prakash