Accenture Global Solutions Limited

Avishek Gulshan

Srikanth G Rao

Tarun Singhal

Ranjana Bhalchandra Narawane

Dongay Choudary Nuvvula

Mathangi Sandilya

Arunabh Sinha

Jayaprakash Nooji Shekar

Gauri S Chikodi

Saisandeep Sanku

A dynamic application testing and scoring system that tests applications under various tenets and categorizes the applications to be published, to be further reviewed or rejected. The results from administering a plurality of tests to an application are analyzed by applying rulesets that pertain to criteria under each of the tenets. An application score is determined from the analysis using weights associated with the tenets, priority levels of the criteria and the severity levels of the rulesets. The application score identifies a position for the application on a scoring scale relative to two trust threshold values. The application is categorized based on the position. Feedback regarding the categorization is received and the trust threshold values on the scoring scale can be adjusted if the categorization in the feedback is different from the categorization produced by the scoring system.

Artificial intelligence based application testing and scoring

Methods and systems including computer programs encoded on a computer storage medium, for receiving a request for digital content to be provided from a plurality of items of digital content, determining a set of content scores for each item of digital content in the plurality of items of digital content, each content score in the set of content scores being specific to a user of the plurality of users, and a respective item of digital content, calculating a combined score deviation for each item of digital content based on a difference between a minimum content score and a maximum content score of the set of content scores of a respective item of digital content, determining at least one candidate item of digital content, the at least one candidate item of digital content having a lowest combined score deviation among combined score deviations of the plurality of items of digital content, and providing the at least one candidate item of digital content.

Intelligent content recommender for groups of users

An intelligent VR (IVR) system receives a VR content item and automatically augments the VR content item with additional or ancillary content. The intelligent VR system initially identifies within the VR content item, valid textual and non-textual objects that have ancillary content associated therewith. The IVR system provides hotspots that signify presence of the ancillary content for the valid objects during a display of the VR content item. The hotspots and the ancillary content are positioned for display corresponding to pixel blocks including the valid objects. The ancillary content is selected for the hotspots based on a spatial and temporal extent of display of the valid objects. The hotspots with respective ancillary content items and the VR content item are streamed to a head mounted display (HMD) for display to a viewer.

Intelligent object recognizer

Growing community of inventors

Bengaluru, India

Avishek Gulshan