Accenture Global Solutions Limited

Badrinath Parameswar

Koushik M Vijayaraghavan

Aditi Kulkarni

Bhaskar Ghosh

Rajendra Prasad Tanniru

Purnima Jagannathan

Luke Higgins

Pradeep Senapati

Jeffson Felix Dsouza

Parul Jagtap

Sangeetha Jayaram

Anthony R Webb

Mahesh Zurale

Genevieve Elizabeth Kuai Ying Lee

Ramanathan Venkataraman

Gaurav Sood

Ranjith Tharayil

Rajendra Tanniru Prasad

Manas Mishra

Gaurav Goenka

Vaijayanthi Ramaswamy

In some implementations, a scheduling platform may receive task information regarding a set of tasks for execution using a set of computing resources, wherein the task information includes, for the set of tasks, at least one of: a run time parameter, a priority parameter, or a success rate parameter. The scheduling platform may communicate with a computing resource management device to obtain first computing resource information regarding the set of computing resources. The scheduling platform may generate a first assignment of the set of tasks to the set of computing resources. The scheduling platform may transmit assignment information identifying the first assignment. The scheduling platform may receive second computing resource information. The scheduling platform may generate a second assignment of the set of tasks to the set of computing resources. The scheduling platform may transmit second assignment information identifying the second assignment.

Dynamic scheduling platform for automated computing tasks

A system may receive enterprise information associated with a client enterprise. The system may select, using an industry analysis model, a set of queries associated with obtaining status information that is associated with a technology profile of the client enterprise. The system may generate client data that is associated with the enterprise information and the status information. The system may convert, using a matrix factorization technique, the client data associated with the client enterprise to a client matrix. The system may convert, using the matrix factorization technique, reference data associated with reference enterprises to a reference matrix. The system may determine, based on a comparison of the client matrix and the reference matrix, a set of scores associated with technology metrics of the technology profile. The system may perform an action associated with the client enterprise based on the set of scores.

Enterprise management system using artificial intelligence and machine learning for technology analysis and integration

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Chennai, India

Badrinath Parameswar