Patents by Inventor Ajmal Karuthakantakath

Ajmal Karuthakantakath 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).

  • Publication number: 20230359986
    Abstract: Disclosed embodiments provide systems and techniques for mass execution of analytical models across multiple dimensions of client, collateral, deal structure, third party, and other data relevant to predicting optimal decisions in real-time. In some embodiments, disclosed systems and techniques increase decisioning speed through the reduction of computational loads on disclosed decisioning systems. Further disclosed systems and techniques may scale-out analytical modeling computations through, among other technological solutions, advanced execution environments that are asynchronous and non-blocking in nature so as to allow the execution of a plurality of analytical models in parallel and optimizing the results.
    Type: Application
    Filed: May 12, 2023
    Publication date: November 9, 2023
    Applicant: Capital One Services, LLC
    Inventors: Chandra DHANDAPANI, Raman BAJAJ, Gurmeet SINGH, Ajmal KARUTHAKANTAKATH, Frederick CRABLE, Nicholas DOLLE, Vikramaditya REPAKA, Sanjiv YAJNIK
  • Patent number: 11709763
    Abstract: Systems and methods are disclosed herein for improving data migration operations including testing and setup of computing environments. In one example, the method may include receiving data for one or more application programming interfaces (APIs). The method may further include generating one or more tests to test the one or more APIs in a first computing environment, testing the APIs, storing the results in a database, and performing a change data capture operation. The method may further include augmenting the one or more tests with the CDC data to generate an updated test. The method may further include testing, using the updated test, a second set of the one or more APIs and comparing the test results. The method may also include outputting a confidence score indicating a correlation between the first environment and the second environment.
    Type: Grant
    Filed: November 22, 2021
    Date of Patent: July 25, 2023
    Assignee: Capital One Services, LLC
    Inventors: Raghuram Madiraju, Palak Mathur, Maz Jawed Baig, Devi Kiran Gonuguntla, Ajmal Karuthakantakath
  • Patent number: 11694156
    Abstract: Disclosed embodiments provide systems and techniques for mass execution of analytical models across multiple dimensions of client, collateral, deal structure, third party, and other data relevant to predicting optimal decisions in real-time. In some embodiments, disclosed systems and techniques increase decisioning speed through the reduction of computational loads on disclosed decisioning systems. Further disclosed systems and techniques may scale-out analytical modeling computations through, among other technological solutions, advanced execution environments that are asynchronous and non-blocking in nature so as to allow the execution of a plurality of analytical models in parallel and optimizing the results.
    Type: Grant
    Filed: December 28, 2020
    Date of Patent: July 4, 2023
    Assignee: Capital One Services, LLC
    Inventors: Chandra Dhandapani, Raman Bajaj, Gurmeet Singh, Ajmal Karuthakantakath, Fredrick Crable, Nicholas Dolle, Vikramaditya Repaka, Sanjiv Yajnik
  • Publication number: 20220129370
    Abstract: Systems and methods are disclosed herein for improving data migration operations including testing and setup of computing environments. In one example, the method may include receiving data for one or more application programming interfaces (APIs). The method may further include generating one or more tests to test the one or more APIs in a first computing environment, testing the APIs, storing the results in a database, and performing a change data capture operation. The method may further include augmenting the one or more tests with the CDC data to generate an updated test. The method may further include testing, using the updated test, a second set of the one or more APIs and comparing the test results. The method may also include outputting a confidence score indicating a correlation between the first environment and the second environment.
    Type: Application
    Filed: November 22, 2021
    Publication date: April 28, 2022
    Applicant: Capital One Services, LLC
    Inventors: Raghuram MADIRAJU, Palak MATHUR, Maz Jawed BAIG, Devi Kiran GONUGUNTLA, Ajmal KARUTHAKANTAKATH
  • Patent number: 11182275
    Abstract: Systems and methods are disclosed herein for improving data migration operations including testing and setup of computing environments. In one example, the method may include receiving data for one or more application programming interfaces (APIs). The method may further include generating one or more tests to test the one or more APIs in a first computing environment, testing the APIs, storing the results in a database, and performing a change data capture operation. The method may further include augmenting the one or more tests with the CDC data to generate an updated test. The method may further include testing, using the updated test, a second set of the one or more APIs and comparing the test results. The method may also include outputting a confidence score indicating a correlation between the first environment and the second environment.
    Type: Grant
    Filed: October 23, 2020
    Date of Patent: November 23, 2021
    Assignee: Capital One Services, LLC
    Inventors: Raghuram Madiraju, Palak Mathur, Maz Jawed Baig, Devi Kiran Gonuguntla, Ajmal Karuthakantakath
  • Publication number: 20210192437
    Abstract: Disclosed embodiments provide systems and techniques for mass execution of analytical models across multiple dimensions of client, collateral, deal structure, third party, and other data relevant to predicting optimal decisions in real-time. In some embodiments, disclosed systems and techniques increase decisioning speed through the reduction of computational loads on disclosed decisioning systems. Further disclosed systems and techniques may scale-out analytical modeling computations through, among other technological solutions, advanced execution environments that are asynchronous and non-blocking in nature so as to allow the execution of a plurality of analytical models in parallel and optimizing the results.
    Type: Application
    Filed: December 28, 2020
    Publication date: June 24, 2021
    Applicant: Capital One Services, LLC
    Inventors: Chandra Dhandapani, Raman Bajaj, Gurmeet Singh, Ajmal Karuthakantakath, Fredrick Crable, Nicholas Dolle, Vikramaditya Repaka, Sanjiv Yajnik
  • Patent number: 10878375
    Abstract: Disclosed embodiments provide systems and techniques for mass execution of analytical models across multiple dimensions of client, collateral, deal structure, third party, and other data relevant to predicting optimal decisions in real-time. In some embodiments, disclosed systems and techniques increase decisioning speed through the reduction of computational loads on disclosed decisioning systems. Further disclosed systems and techniques may scale-out analytical modeling computations through, among other technological solutions, advanced execution environments that are asynchronous and non-blocking in nature so as to allow the execution of a plurality of analytical models in parallel and optimizing the results.
    Type: Grant
    Filed: November 15, 2018
    Date of Patent: December 29, 2020
    Assignee: CAPITAL ONE SERVICES, LLC
    Inventors: Chandra Dhandapani, Raman Bajaj, Gurmeet Singh, Ajmal Karuthakantakath, Fredrick Crable, Nicholas Dolle, Vikramaditya Repaka, Sanjiv Yajnik
  • Patent number: 10719374
    Abstract: Aspects described herein may allow for the application of dynamically generating APIs using API generator based on database metadata. An API generator may extract metadata associated with store procedures. The API generator may generate a first layer of API that communicates with an enterprise application via a first data format. The API generator may generate a second layer of the API that communicates with a database via a second data format. The API generator may receive a request to invoke a stored procedure in a first data format. In response to receiving the request, the generated API may generate a converted request in the second data format.
    Type: Grant
    Filed: September 17, 2019
    Date of Patent: July 21, 2020
    Assignee: Capital One Services, LLC
    Inventors: Palak Mathur, Jacques Morel, Trent Jones, Jordan Donais, Maz Baig, Ajmal Karuthakantakath, Devi Kiran Gonuguntla, Raghuram Madiraju, Suresh Navayamkunnil Raghavan
  • Publication number: 20190087773
    Abstract: Disclosed embodiments provide systems and techniques for mass execution of analytical models across multiple dimensions of client, collateral, deal structure, third party, and other data relevant to predicting optimal decisions in real-time. In some embodiments, disclosed systems and techniques increase decisioning speed through the reduction of computational loads on disclosed decisioning systems. Further disclosed systems and techniques may scale-out analytical modeling computations through, among other technological solutions, advanced execution environments that are asynchronous and non-blocking in nature so as to allow the execution of a plurality of analytical models in parallel and optimizing the results.
    Type: Application
    Filed: November 15, 2018
    Publication date: March 21, 2019
    Applicant: Capital One Services, LLC
    Inventors: Chandra Dhandapani, Raman Bajaj, Gurmeet Singh, Ajmal Karuthakantakath, Fredrick Crable, Nicholas Dolle, Vikramaditya Repaka, Sanjiv Yajnik
  • Patent number: 10163072
    Abstract: Disclosed embodiments provide systems and techniques for mass execution of analytical models across multiple dimensions of client, collateral, deal structure, third party, and other data relevant to predicting optimal decisions in real-time. In some embodiments, disclosed systems and techniques increase decisioning speed through the reduction of computational loads on disclosed decisioning systems. Further disclosed systems and techniques may scale-out analytical modeling computations through, among other technological solutions, advanced execution environments that are asynchronous and non-blocking in nature so as to allow the execution of a plurality of analytical models in parallel and optimizing the results.
    Type: Grant
    Filed: April 17, 2018
    Date of Patent: December 25, 2018
    Assignee: CAPITAL ONE SERVICES, LLC
    Inventors: Chandra Dhandapani, Raman Bajaj, Gurmeet Singh, Ajmal Karuthakantakath, Fredrick Crable, Nicholas Dolle, Vikramaditya Repaka, Sanjiv Yajnik
  • Publication number: 20180232691
    Abstract: Disclosed embodiments provide systems and techniques for mass execution of analytical models across multiple dimensions of client, collateral, deal structure, third party, and other data relevant to predicting optimal decisions in real-time. In some embodiments, disclosed systems and techniques increase decisioning speed through the reduction of computational loads on disclosed decisioning systems. Further disclosed systems and techniques may scale-out analytical modeling computations through, among other technological solutions, advanced execution environments that are asynchronous and non-blocking in nature so as to allow the execution of a plurality of analytical models in parallel and optimizing the results.
    Type: Application
    Filed: April 17, 2018
    Publication date: August 16, 2018
    Inventors: Chandra Dhandapani, Raman Bajaj, Gurmeet Singh, Ajmal Karuthakantakath, Fredrick Crable, Nicholas Dolle, Vikramaditya Repaka, Sanjiv Yajnik
  • Patent number: 9978038
    Abstract: Disclosed embodiments provide systems and techniques for mass execution of analytical models across multiple dimensions of client, collateral, deal structure, third party, and other data relevant to predicting optimal decisions in real-time. In some embodiments, disclosed systems and techniques increase decisioning speed through the reduction of computational loads on disclosed decisioning systems. Further disclosed systems and techniques may scale-out analytical modeling computations through, among other technological solutions, advanced execution environments that are asynchronous and non-blocking in nature so as to allow the execution of a plurality of analytical models in parallel and optimizing the results.
    Type: Grant
    Filed: September 19, 2017
    Date of Patent: May 22, 2018
    Assignee: Capital One Services, LLC
    Inventors: Chandra Dhandapani, Raman Bajaj, Gurmeet Singh, Ajmal Karuthakantakath, Fredrick Crable, Nicholas Dolle, Vikramaditya Repaka, Sanjiv Yajnik
  • Patent number: 9965741
    Abstract: Disclosed embodiments provide systems and techniques for mass execution of analytical models across multiple dimensions of client, collateral, deal structure, third party, and other data relevant to predicting optimal decisions in real-time. In some embodiments, disclosed systems and techniques increase decisioning speed through the reduction of computational loads on disclosed decisioning systems. Further disclosed systems and techniques may scale-out analytical modeling computations through, among other technological solutions, advanced execution environments that are asynchronous and non-blocking in nature so as to allow the execution of a plurality of analytical models in parallel and optimizing the results.
    Type: Grant
    Filed: December 16, 2016
    Date of Patent: May 8, 2018
    Assignee: Capital One Services, LLC
    Inventors: Chandra Dhandapani, Raman Bajaj, Gurmeet Singh, Ajmal Karuthakantakath, Fred Crable, Nicholas Dolle, Vikramaditya Repaka, Sanjiv Yajnik
  • Publication number: 20180005179
    Abstract: Disclosed embodiments provide systems and techniques for mass execution of analytical models across multiple dimensions of client, collateral, deal structure, third party, and other data relevant to predicting optimal decisions in real-time. In some embodiments, disclosed systems and techniques increase decisioning speed through the reduction of computational loads on disclosed decisioning systems. Further disclosed systems and techniques may scale-out analytical modeling computations through, among other technological solutions, advanced execution environments that are asynchronous and non-blocking in nature so as to allow the execution of a plurality of analytical models in parallel and optimizing the results.
    Type: Application
    Filed: September 19, 2017
    Publication date: January 4, 2018
    Inventors: Chandra Dhandapani, Raman Bajaj, Gurmeet Singh, Ajmal Karuthakantakath, Fred Crable, Nicholas Dolle, Vikramaditya Repaka, Sanjiv Yajnik
  • Publication number: 20170178063
    Abstract: Disclosed embodiments provide systems and techniques for mass execution of analytical models across multiple dimensions of client, collateral, deal structure, third party, and other data relevant to predicting optimal decisions in real-time. In some embodiments, disclosed systems and techniques increase decisioning speed through the reduction of computational loads on disclosed decisioning systems. Further disclosed systems and techniques may scale-out analytical modeling computations through, among other technological solutions, advanced execution environments that are asynchronous and non-blocking in nature so as to allow the execution of a plurality of analytical models in parallel and optimizing the results.
    Type: Application
    Filed: December 16, 2016
    Publication date: June 22, 2017
    Inventors: Chandra Dhandapani, Raman Bajaj, Gurmeet Singh, Ajmal Karuthakantakath, Fred Crable, Nicholas Dolle, Vikramaditya Repaka, Sanjiv Yajnik