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Unveiling of RISHI-XAI by Digité

Digité, Inc. recently launched RISHI-the world’s first XAI (eXplainable Artificial Intelligence) enabled product for large enterprises in Bangalore amidst the presence of its leadership team and a few esteemed media personalities. Already a leader in Lean/ Agile Application Lifecycle Management Products, Digité, Inc.’s latest innovation is the world’s first Explainable Artificial Intelligence driven tracker for successful project management and predict its performance thereby using what-if analysis to take corrective actions against predicted challenges.

A.V. Sridhar, CEO & Co-founder of Digité, Inc. while unveiling the product stated “One of the fundamental problems of adopting AI/ML at scale is that the current generation of black box-AI products do a very poor job of explaining results to the end user. Keeping that in mind, we have built RISHI with eXplainable AI (XAI) capabilities to effectively drive AI adoption within the enterprise." He also explained “Using RISHI, enterprises will be able to leverage the vast amounts of data that their project delivery and other operational systems already contain - and gain dramatic capability to predict likely deviations in critical success parameters of projects and programs, perform what-if analysis of several corrective actions - and then implement the most effective options to bring the projects and programs back on track and improve profitability.”

The event was also addressed by Dr. Ramesh Patil, Parameshwaran CR, and Mahesh Singh who all explained the various aspects of RISHI and how it will revolutionize project management in the years to come. They also addressed the Q&A sessions with the media thereafter.

In order to better understand RISHI, it is imperative to understand the agile model of Project Management to start with. As and when every sprint progresses, RISHI calculates the Velocity and Quality as part of the Performance Indicator and using XAI predicts that of the future sprints and identify deviations and recommends steps to improve the overall performance of the upcoming sprints. RISHI works at various levels including Work Items, Project ad Delivery Units and its foundation is based on a repository of collected data from various real life scenarios of organizations. RISHI has been designed in such a way that it provides decision makers “data provenance” (data traceability) and visibility into “feature engineering” enabling “Root Cause Analysis (RCA)” into the factors affecting the overall project performance.

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