Intelligent Decisioning

Intelligent Decisioning is a predictive analytics platform built for driving software testing process intelligence. Software testing conventionally looks at validating requirements and ignoring the correlation of data points that can be extracted from test results, test processes, defect logs, developer and testers performance, production incidents, code coverage, environment factors and sentiment of product users in real life situations. Intelligent Decisioning platform draws insights from these data points and enables AI (Machine Learning) based decisioning to reduce software defects, thus surpassing traditional testing practices and driving process and performance efficiencies.

This platform can be used to predict probability of meeting Testing objectives - Delivered Defects, completion within Testing Schedule and Effort and identify which phases of Testing require higher controls and monitoring. Built on technologies like Java, R and Python(AI/ML), this platform augments human decisioning through descriptive, predictive and prescriptive analytics.

Use Cases

ARCHITECTURE

Case Studies

Our clients have been able to identify number of improvement opportunities through implementation of Intelligent Decisioning

16% REDUCTION IN CYCLE TIME WITH EARY DEFECT DETECTION FOR ALL CRITICAL AND HIGH SEVERITY DEFECTS FOR A LEADING CLIENT IN FINANCE INDUSTRY

Challenges

  • Improve planning activity to estimate the release time accurately
  • Efficient optimization of test cases for efforts reduction
  • Too much time is being taken to detect defects

Our solution

  • Leveraged Intelligent Decisioning to use predictive analytics for upcoming release for better planning
  • Leveraged Intelligent Decisioning to identify risk prone areas
  • Efficient optimization of test suite
  • Early defect detection by prioritizing the test cases

EARLY DEFECT DETECTION FOR ALL DEFECTS BY 40% REDUCTION IN TIMELINE WITH 23% TEST CASE OPTIMIZATION FOR A LEADING CLIENT IN ENTERTAINMENT INDUSTRY

Challenges

  • Improve planning activity to prioritize test cases to cover high risk prone areas at the start
  • Efficient optimization of test cases
  • Too much time is being taken to detect defects

Our solution

  • Leveraged Intelligent Decisioning to identify risk prone areas
  • Efficient optimization of test suite
  • Early defect detection by prioritizing the test cases

BETTER RELEASE PLANNING WITH RELEASE PERFORMANCE PREDICTION RESULTING INTO 70% RAISE IN EARLY DEFECT DETECTION FOR HIGH RISK PRONE AREAS, 16% EFFORT REDUCTION WITH HELP OF TEST CASE OPTIMIZATION AND PRIORITIZATION, AND 80% REDUCTION IN FIX TIME FOR SIMILAR DEFECTS FOR A LEADING CLIENT IN TRADING & LOGISTICS INDUSTRY

Challenges

  • Improve planning activity in estimating release time
  • Efficient optimization of test cases for regression suite
  • Unearth hidden patterns from the historical data
  • Too much time is being taken to close duplicate / similar defects

Our solution

  • Leveraged Intelligent Decisioning for Predictive Analytics for upcoming release
  • Identify Risk prone areas with Risk Index for each area
  • Optimize regression pack (Risk Based Testing)
  • Defect Analysis to explore hidden patterns and find similar defects for quick closure

Contacts

Rohit Patwardhan