Patents by Inventor Deepali Kale

Deepali Kale 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).

  • Methods and systems for implementing a unified data format for artificial intelligence systems
    Patent number: 12386836
    Abstract: Systems and method are provided for artificial-intelligence-based formatting of data into interface-specific representations. A computing device may receive datasets including information structured for presentation through various interfaces. The computing device may train a machine-learning model using feature vectors defined from the datasets. The machine-learning model may be trained to generate interface-specific representations of data. The computing device may then receive a query through a first type of interface and execute the trained machine-learning model using the query and an identification of the first type of interface. The machine-learning model may generate a response to the query that includes a structure tailored for interfaces that correspond to the first type of interface. The computing device may then facilitate a transmission of the response to the query through an interface that corresponds to the first type of interface.
    Type: Grant
    Filed: December 26, 2023
    Date of Patent: August 12, 2025
    Assignee: LIVEPERSON, INC.
    Inventors: Ranjith Gampa, James Poulin, Jesse Wang, Ravi Gadekarla, Manoj Potturu, Ravikiran Chittari, Akhila Ravela, Deepali Kale, Snigdha Sivadas, Trupti Chinchghare
  • METHODS AND SYSTEMS FOR IMPLEMENTING A UNIFIED DATA FORMAT FOR ARTIFICIAL INTELLIGENCE SYSTEMS
    Publication number: 20240211477
    Abstract: Systems and method are provided for artificial-intelligence-based formatting of data into interface-specific representations. A computing device may receive datasets including information structured for presentation through various interfaces. The computing device may train a machine-learning model using feature vectors defined from the datasets. The machine-learning model may be trained to generate interface-specific representations of data. The computing device may then receive a query through a first type of interface and execute the trained machine-learning model using the query and an identification of the first type of interface. The machine-learning model may generate a response to the query that includes a structure tailored for interfaces that correspond to the first type of interface. The computing device may then facilitate a transmission of the response to the query through an interface that corresponds to the first type of interface.
    Type: Application
    Filed: December 26, 2023
    Publication date: June 27, 2024
    Applicant: LIVEPERSON, INC.
    Inventors: Ranjith Gampa, James Poulin, Jesse Wang, Ravi Gadekarla, Manoj Potturu, Ravikiran Chittari, Akhila Ravela, Deepali Kale, Snigdha Sivadas, Trupti Chinchghare