Accenture Global Solutions Limited

Ravi Kant Gaur

Kishore P Durg

Nirav Sampat

Vinu Varghese

Raghavan Tinniyam Iyer

Ramkumar Kothandaraman

Balaji Janarthanam

Selvakuberan Karuppasamy

Puneet Kalra

Bhavna Butani

Sudeep Sharma

Saumyabrata Mitra

Ragav Devanathan

Dinesh Jaibhagwan Mittal

Praveen Subbnanjappa

Sundharraman Karthik Narain

John Francis Walsh

Anto Jose

Karthik Srikantamurthy

Systems and methods for detecting, classifying, and managing impediments are disclosed. For example, embodiments may be related to impediments in project management. The proposed systems and methods are configured to evaluate data harvested from multiple different sources (in different formats), identify potential impediments that may be described or present in the data, and classify said impediments based on whether the impediment is non-technical or technical. In addition, the proposed systems implement a technical solution of active learning combined with reinforcement learning to produce a feedback loop that, over each iteration, improves the accuracy of the impediment classification. The impediment management assistant is configured to identify impediments from various inputs sources across industries with an AI-based self-learning capability, providing a robust and accurate model even with only a limited training dataset.

Detection and classification of impediments

Methods, systems, and apparatus, including computer programs encoded on computer storage media, for generating a win prediction for an opportunity. In some implementations, a server receives data representing an opportunity. The server obtains historical data from a data repository based on the received data representing the opportunity. The server generates standardized feature vectors based on non-standardized data, the non-standardized data comprising (i) the received data and (ii) the obtained historical data. The server filters the standardized feature vectors. The server generates a win percentage based on the filtered feature vectors using classifiers. In response to generating the win percentage for the opportunity, the server generates a plurality of data insights using the classifiers and the generated win percentage, wherein the plurality of data insights describe one or more data predictions for pursuing the opportunity. The server provides the win percentage and the plurality of data insights for output.

Enhanced data driven intelligent cloud advisor system

Growing community of inventors

Bengaluru, India

Ravi Kant Gaur