Patents by Inventor Srinath Chakinam

Srinath Chakinam 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: 11321161
    Abstract: Artificial Intelligence/Machine Learning-based performance monitoring of database applications to identify performance issues/bottlenecks that may lead to application failure. In response to identifying the performance issues, AI/ML-based analysis of the database is performed to determine the root cause of the performance issues and resolutions for addressing/overcoming the probable causes. As a result, a comprehensive system that capable of monitoring and determining database related performance issues within database application and capable of determining and implementing the resolution to such performance issues. In addition, an auto-correction feature for errors that may occur during the monitoring of the database applications and related analysis.
    Type: Grant
    Filed: February 7, 2020
    Date of Patent: May 3, 2022
    Assignee: BANK OF AMERICA CORPORATION
    Inventors: Ambica Poola, Praveen Kumar Bolla, Trishul Vuppalanchi, Srinath Chakinam
  • Publication number: 20210248024
    Abstract: Artificial Intelligence/Machine Learning-based performance monitoring of database applications to identify performance issues/bottlenecks that may lead to application failure. In response to identifying the performance issues, AI/ML-based analysis of the database is performed to determine the root cause of the performance issues and resolutions for addressing/overcoming the probable causes. As a result, a comprehensive system that capable of monitoring and determining database related performance issues within database application and capable of determining and implementing the resolution to such performance issues. In addition, an auto-correction feature for errors that may occur during the monitoring of the database applications and related analysis.
    Type: Application
    Filed: February 7, 2020
    Publication date: August 12, 2021
    Applicant: BANK OF AMERICA CORPORATION
    Inventors: Ambica Poola, Praveen Kumar Bolla, Trishul Vuppalanchi, Srinath Chakinam
  • Patent number: 10884708
    Abstract: Apparatus and methods for an intelligent audit engine are provided. Product development artifacts may be associated with artifact tags and stored in an artifact repository. The audit engine may retrieve an artifact for audit. The audit engine may identify a set of development guidelines in a rule repository based on their artifact tags. The audit engine may determine whether the development guidelines have been satisfied based on stored product testing data. A failed development guideline may initiate a workflow that includes notification of a project stakeholder regarding the failure. The notification may include remediation measures to be taken by the stakeholder. The validation process may iterate until all guidelines have passed validation. A machine-learning algorithm may prioritize a development guideline for future audits to increase efficiency. The machine learning algorithm may educate stakeholders to reduce audit failures.
    Type: Grant
    Filed: September 19, 2019
    Date of Patent: January 5, 2021
    Assignee: Bank of America Corporation
    Inventors: Srinath Chakinam, Bharathi Tadepalli, Kalyan Chakravarthy Pallapolu
  • Publication number: 20200012479
    Abstract: Apparatus and methods for an intelligent audit engine are provided. Product development artifacts may be associated with artifact tags and stored in an artifact repository. The audit engine may retrieve an artifact for audit. The audit engine may identify a set of development guidelines in a rule repository based on their artifact tags. The audit engine may determine whether the development guidelines have been satisfied based on stored product testing data. A failed development guideline may initiate a workflow that includes notification of a project stakeholder regarding the failure. The notification may include remediation measures to be taken by the stakeholder. The validation process may iterate until all guidelines have passed validation. A machine-learning algorithm may prioritize a development guideline for future audits to increase efficiency. The machine learning algorithm may educate stakeholders to reduce audit failures.
    Type: Application
    Filed: September 19, 2019
    Publication date: January 9, 2020
    Inventors: Srinath Chakinam, Bharathi Tadepalli, Kalyan Chakravarthy Pallapolu
  • Patent number: 10459694
    Abstract: Apparatus and methods for an intelligent audit engine are provided. Product development artifacts may be associated with artifact tags and stored in an artifact repository. The audit engine may retrieve an artifact for audit. The audit engine may identify a set of development guidelines in a rule repository based on their artifact tags. The audit engine may determine whether the development guidelines have been satisfied based on stored product testing data. A failed development guideline may initiate a workflow that includes notification of a project stakeholder regarding the failure. The notification may include remediation measures to be taken by the stakeholder. The validation process may iterate until all guidelines have passed validation. A machine-learning algorithm may prioritize a development guideline for future audits to increase efficiency. The machine learning algorithm may educate stakeholders to reduce audit failures.
    Type: Grant
    Filed: October 16, 2017
    Date of Patent: October 29, 2019
    Assignee: Bank of America Corporation
    Inventors: Srinath Chakinam, Bharathi Tadepalli, Kalyan Chakravarthy Pallapolu
  • Publication number: 20190114148
    Abstract: Apparatus and methods for an intelligent audit engine are provided. Product development artifacts may be associated with artifact tags and stored in an artifact repository. The audit engine may retrieve an artifact for audit. The audit engine may identify a set of development guidelines in a rule repository based on their artifact tags. The audit engine may determine whether the development guidelines have been satisfied based on stored product testing data. A failed development guideline may initiate a workflow that includes notification of a project stakeholder regarding the failure. The notification may include remediation measures to be taken by the stakeholder. The validation process may iterate until all guidelines have passed validation. A machine-learning algorithm may prioritize a development guideline for future audits to increase efficiency. The machine learning algorithm may educate stakeholders to reduce audit failures.
    Type: Application
    Filed: October 16, 2017
    Publication date: April 18, 2019
    Inventors: Srinath Chakinam, Bharathi Tadepalli, Kalyan Chakravarthy Pallapolu