Abstract
Agile software development tools have been created to assist project management and enhance productivity. However, it may be challenging to properly employ those tools, especially in a hybrid work environment. Techniques are presented herein, which may be referred to herein as a MaPM system, that leverage a conferencing platform to offer a real-time agile project risk management and prediction framework that utilizes multi-modal collaboration data sources. Aspects of the presented techniques encompass an artificial intelligence (AI)-backed summarization model that may be utilized to extract project details and an auto-agile that model may consume those loggings and generate the predicted project sprint backlogs and their risks. Further aspects of the presented techniques support an optimization module that may jointly update the predicted sprint backlogs and the estimated task risks to realize the finalized backlog sequences. In summary, an MaPM system, according to the presented techniques, offers four novelties compared with conventional agile project management tools – a conferencing platform-centralized solution for automatic agile project risk prediction and management, a real-time multi-modal-based project risk monitoring and prediction system, the generation of sprint backlogs based on fully evaluated contexts that are collected from all of a project’s participants, and the liberation of project contributors from having to conduct manual project tracking and recording.
Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 License.
Recommended Citation
Sun, Pengfei and Shao, Qihong, "MAPM: MULTI-MODAL AUTO-AGILE PROJECT RISK MANAGEMENT AND PREDICTION FOR COLLABORATION PLATFORM USING AI/ML", Technical Disclosure Commons, (May 22, 2023)
https://www.tdcommons.org/dpubs_series/5912