The patent badge is an abbreviated version of the USPTO patent document. The patent badge does contain a link to the full patent document.

The patent badge is an abbreviated version of the USPTO patent document. The patent badge covers the following: Patent number, Date patent was issued, Date patent was filed, Title of the patent, Applicant, Inventor, Assignee, Attorney firm, Primary examiner, Assistant examiner, CPCs, and Abstract. The patent badge does contain a link to the full patent document (in Adobe Acrobat format, aka pdf). To download or print any patent click here.

Date of Patent:
Jul. 08, 2025

Filed:

Jun. 21, 2022
Applicant:

Accenture Global Solutions Limited, Dublin, IE;

Inventors:

Vinu Varghese, Bangalore, IN;

Anto Jose, Thodupuzha, IN;

Balaji Janarthanam, Chennai, IN;

Selvakuberan Karuppasamy, Chennai, IN;

Saumyabrata Mitra, Kolkata, IN;

Karthik Srikantamurthy, Mysuru, IN;

Ravi Kant Gaur, Bangalore, IN;

Ragav Devanathan, Chennai, IN;

Nirav Jagdish Sampat, Mumbai, IN;

Assignee:
Attorney:
Primary Examiner:
Int. Cl.
CPC ...
G06Q 10/0631 (2023.01);
U.S. Cl.
CPC ...
G06Q 10/06312 (2013.01); G06Q 10/063114 (2013.01);
Abstract

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.


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