Bank of America Corporation

Wells Fargo Bank, N.a.

Aditya Kulkarni

Venugopala Rao Randhi

Rama Venkata S Kavali

Lawrence Anthony D'Silva

Vishal Wadhwa

Sunil Reddy Gaddam

Mangesh Narendra Chore

Sai Raghavendra Neralla

Marimuthu Muthan

Ganesh Kumar

Jashua Thejas Arul Dhas

Anshul Chauhan

Systems, computer program products, and methods are described herein for device configuration data generation and management via a machine learning engine. The present invention is configured to receive credentials on an interface of an endpoint device, receive a request from the endpoint device to access a portal, authenticate the credentials via an authentication engine, receive specifications, wherein the specifications are input into the interface of the endpoint device, select, via a configuration engine comprising pre-existing configurations in a configuration database of a first storage device, a selected pre-existing configuration, determine a verification of the selected pre-existing configuration, and access the portal.

System and method for device configuration data generation and management via a machine learning engine

An example system can include: at least one processor; and non-transitory computer-readable storage storing instructions that, when executed by the at least one processor, cause the system to: generate an ingestion manager programmed to ingest data associated with a job; and generate a logging manager programmed to capture metadata associated with the job; wherein the ingestion manager is programmed to automatically retry the job based upon the metadata captured by the logging manager.

Management of ingestion jobs using automated retry

A method includes receiving a plurality of data processing requests and generating a primary processing stack indicating a queue for processing the first data. The primary processing stack comprises a plurality of layers. Each layer comprises a plurality of slices, wherein each slice represents a portion of the first data of at least one data processing request. The plurality of slices are arranged within each layer based at least on the priority indicator corresponding to the first data that each slice represents. The method further includes receiving resource information about a plurality of servers, assigning each slice of the primary processing stack to one of the servers, and sending processing instructions comprising an identification of each slice of the primary processing stack assigned to the respective server.

Resource allocation tool

A method includes receiving a plurality of data processing requests and assigning each data processing request to a group based on the source of the data. The method further includes generating a primary processing stack indicating a queue for processing the first data, wherein: the primary processing stack comprises a plurality of layers; each layer comprises a plurality of slices, wherein each slice represents a portion of the first data of at least one data processing request; and the plurality of slices are arranged within each layer based at least on the priority indicator corresponding to the first data that each slice represents. The method further includes receiving resource information about a plurality of servers, assigning each slice of the primary processing stack to one of the servers, and sending processing instructions comprising an identification of each slice of the primary processing stack assigned to the respective server.

Growing community of inventors

Hyderabad Telangana, India

Aditya Kulkarni