Patents by Inventor Brian Daniel Luskey

Brian Daniel Luskey 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).

  • System and method for artificial intelligence driven document analysis, including automated reuse of predictive coding rules based on management and curation of datasets or models
    Patent number: 12437240
    Abstract: Artificial intelligence based document analysis systems and methods are disclosed. Embodiments of document analysis systems may allow the reuse of coded datasets defined in association with a particular code by allowing these datasets to be bundled to define a dataset for another code, where that code may be associated with a target corpus of documents. A model can then be trained based on that dataset and used to provide predictive scores for the documents of the target corpora with respect to the code. Furthermore, this code can be applied not just to the target corpus of documents, but additionally can be applied against any other corpora.
    Type: Grant
    Filed: July 7, 2022
    Date of Patent: October 7, 2025
    Assignee: CS Disco, Inc.
    Inventors: Alan Justin Lockett, Verlyn Michael Fischer, Richard Alan Vestal, Jesse Abraham Ramos, Robert Duane Harrington, Brian Daniel Luskey
  • SYSTEM AND METHOD FOR ARTIFICIAL INTELLIGENCE DRIVEN DOCUMENT ANALYSIS, INCLUDING AUTOMATED REUSE OF PREDICTIVE CODING RULES BASED ON MANAGEMENT AND CURATION OF DATASETS OR MODELS
    Publication number: 20230004873
    Abstract: Artificial intelligence based document analysis systems and methods are disclosed. Embodiments of document analysis systems may allow the reuse of coded datasets defined in association with a particular code by allowing these datasets to be bundled to define a dataset for another code, where that code may be associated with a target corpus of documents. A model can then be trained based on that dataset and used to provide predictive scores for the documents of the target corpora with respect to the code. Furthermore, this code can be applied not just to the target corpus of documents, but additionally can be applied against any other corpora.
    Type: Application
    Filed: July 7, 2022
    Publication date: January 5, 2023
    Inventors: Alan Justin Lockett, Verlyn Michael Fischer, Richard Alan Vestal, Jesse Abraham Ramos, Robert Duane Harrington, Brian Daniel Luskey
  • System and method for artificial intelligence driven document analysis, including automated reuse of predictive coding rules based on management and curation of datasets or models
    Patent number: 11416685
    Abstract: Artificial intelligence based document analysis systems and methods are disclosed. Embodiments of document analysis systems may allow the reuse of coded datasets defined in association with a particular code by allowing these datasets to be bundled to define a dataset for another code, where that code may be associated with a target corpus of documents. A model can then be trained based on that dataset and used to provide predictive scores for the documents of the target corpora with respect to the code. Furthermore, this code can be applied not just to the target corpus of documents, but additionally can be applied against any other corpora.
    Type: Grant
    Filed: May 22, 2020
    Date of Patent: August 16, 2022
    Assignee: CS DISCO, INC.
    Inventors: Alan Justin Lockett, Verlyn Michael Fischer, Richard Alan Vestal, Jesse Abraham Ramos, Robert Duane Harrington, Brian Daniel Luskey
  • SYSTEM AND METHOD FOR ARTIFICIAL INTELLIGENCE DRIVEN DOCUMENT ANALYSIS, INCLUDING AUTOMATED REUSE OF PREDICTIVE CODING RULES BASED ON MANAGEMENT AND CURATION OF DATASETS OR MODELS
    Publication number: 20210240937
    Abstract: Artificial intelligence based document analysis systems and methods are disclosed. Embodiments of document analysis systems may allow the reuse of coded datasets defined in association with a particular code by allowing these datasets to be bundled to define a dataset for another code, where that code may be associated with a target corpus of documents. A model can then be trained based on that dataset and used to provide predictive scores for the documents of the target corpora with respect to the code. Furthermore, this code can be applied not just to the target corpus of documents, but additionally can be applied against any other corpora.
    Type: Application
    Filed: May 22, 2020
    Publication date: August 5, 2021
    Inventors: Alan Justin Lockett, Verlyn Michael Fischer, Richard Alan Vestal, Jesse Abraham Ramos, Robert Duane Harrington, Brian Daniel Luskey