What is RISHI-XAI?
RISHI-XAI is Digite’s next generation XAI (eXplainable AI) enabled Enterprise Project Intelligence product that caters to CXO’s, Delivery Heads, Project Managers and other decision makers. It combines a knowledge system crafted from Digite’s vast domain experience, a cutting-edge machine learning system and eXplainable AI.
RISHI-XAI is an advanced Artificial Intelligence/ Machine Learning based solution that “listens” to and learns from your performance data, and predicts what is likely to happen with your current projects.
RISHI-XAI’s design has an innovative automated pipeline that provides users data provenance (data traceability) and visibility into feature engineering, enabling Root Cause Analysis (RCA) into the factors affecting project performance. These help one understand the deviations in key indicators that drive enterprise success.
Why RISHI-XAI?Helps you make decisions!
For meaningful insights, one has to analyze vast amounts of past, present and near real-time data which is humanly not possible. For the first time grappling with myriad business complexities in real-time is possible. RISHI-XAI gives you –
- AI/ ML assisted Project Management
- Multiple What-If scenarios
- Actionable insights based on your data
RISHI Transforms Your Organization
By providing a smart way to manage programs
SwiftEnterprise has the ability to track agile, traditional (waterfall/ iterative) and hybrid projects together. RISHI-XAI extracts learnings from large volumes of your organization’s project execution data and applies it to ongoing projects so that one is given actionable insights about future outcomes on time.
By introducing granular program management
As one would agree, organizations today have programs with a wide variety of projects being executed. Normally a program cuts across various project types thereby making it difficult to get a blended view of the outcomes. RISHI-XAI overcomes this problem for our customers. RISHI-XAI uses a bottom-up approach to program management by leveraging AI/ ML to calculate program goal deviations right down to a granular level.
By driving project decision-making with the XAI engine
RISHI’s XAI component not only quantifies the reasons why project performance might deteriorate in the future but also puts you in the driver’s seat by suggesting which areas need action, such as increasing design effort or improving testing effectiveness, and by how much!
By using cross-functional data in project decision making
With RISHI-XAI’s data lake, you can connect your organization’s ERP, DevOps and Revenue Solutions and leverage project management data to control both the top-line and bottom-line of your organization.
Multi-Scenario Role-based What-If Analysis
Decision makers can set macro to micro level goals across projects by using RISHI-XAI’s powerful ‘What-If Scenario Analysis’ feature. This would help the users with different roles to track project goal deviations, on a near real time basis. RISHI-XAI suggests actions that users could implement to reach the ‘set goals’. Further, they can visualize the impact of these actions before actually implementing them.
RISHI-XAI’s Unique Features
For existing customers of Digite’s Swift suite of products, RISHI-XAI comes enabled with an ecosystem of chatbots which allow users to interact intelligently with the system . We bring the latest in NLP technologies to our customers.
Domain Specific ML Models
Our AI models are built on large volumes of project execution data which makes it more robust. RISHI-XAI is shipped with factory models of multiple project types, like Agile, Maintenance, Testing, DevOps etc.
Connects to your Existing ALM products
The time to accrue benefits from RISHI-XAI is short because it connects to existing ALM products that an organization or its customers use. Implementing RISHI-XAI does not need a large migration process to leverage its predictive and XAI capabilities.
Handcrafted Knowledge System
RISHI-XAI is not a generic AI/ ML product. It is domain specific and is an outcome of the knowledge gained by Digite over the last 18+ years operating in the IT space. It improves its Machine Learning based suggestions through a handcrafted knowledge system using an industry-specific Ontological framework.
Constructed with Microservices architecture
RISHI-XAI uses a cloud based microservices architecture. This enables a robust framework, so that results of analyses can be extracted using APIs. In addition to this, upgraded versions of RISHI_XAI can be deployed with minimal downtime. This architecture also allows for easy customization across projects and customers.
Most program and project management systems deal with structured data such as tasks, work breakdown structures (WBS), cost and resources. They do not address soft-factors such as the team’s interactions, motivation and emotional state. As an optional add-on, RISHI-XAI’s Team Dynamics enables our AI Models to consider these soft factors.