Dell Products Inc.

Emc IP Holding Company LLC

Sourav Datta

Hung The Dinh

Sashibhusan Panda

Seshadri Srinivasan

Shishir Kumar Parhi

Lakshman Kumar Tiwari

Bijan Kumar Mohanty

Puneet Kumar Arora

Sabu K Syed

Panguluru Vijaya Sekhar

Rajesh Krishnan

Manikandan Pammal Rathinavelu

Vijaya Panguluru Sekhar

Shivangi Geetanjali

Sambasivarao Gaddam

Antarlina Tripathy

Baishali Roy

Sweta Kumari

Kiran Kumar Pidugu

Geetha Venkatesan

Muhammed Mohiuddin

Ranjani Muthyam Venkata

Sowmya K

Venkata Nagendra Purushotham Musti

Yash Khare

A method comprises collecting data corresponding to one or more code changes in response to committing of the one or more code changes to a code repository, and formatting the data into at least one data string. The at least one data string is inputted to one or machine learning models. Using the one or machine learning models, a natural language description of the one or more code changes is generated based at least in part on the at least one data string. The method further comprises causing transmission of the natural language description of the one or more code changes to a document repository.

Code modification management using machine learning

A method comprises managing multiple tasks of multiple entities associated with a deployment of a software program with a deployment framework comprising a machine learning module configured to assist with managing the multiple tasks of the multiple entities. The managing step comprises tracking a status of one or more of the multiple tasks, and predicting a time taken for a given one of the multiple entities to complete a given one of the multiple tasks.

Enterprise deployment framework with artificial intelligence/machine learning

Methods, apparatus, and processor-readable storage media for transaction visibility framework implemented using artificial intelligence are provided herein. An example computer-implemented method includes monitoring data related to a transaction flow across multiple layers of an enterprise system; determining which of the multiple layers correspond to at least one detected problem within the transaction flow by applying artificial intelligence techniques to the data; generating a visualization of the transaction flow, wherein generating the visualization comprises generating a sequential view of the transaction flow, generating one or more parallel sub-transaction flows pertaining to one or more dependencies of the transaction flow, and producing a visual indication of the detected problem; determining, based on analyzing the generated visualization, one or more automated actions related to the detected problem and the determined layer of the enterprise system corresponding to the detected problem; and automatically initiating the one or more automated actions.

Transaction visibility frameworks implemented using artificial intelligence

Growing community of inventors

Bengaluru, India

Sourav Datta