Lack of Test Case and Real-life Scenario manifestation.
Low Test automation adoption.
Insufficient project based Test Case Inventory and Pipeline automation.
Very low optimization across the Test environment
AI driven test optimization technology to minimize and accelerate testing while providing a predictive outcome.
Defect Predict - Python pattern recognition to make data-driven prediction
Defect Classify - Python natural language classification to reduce defect turnaround
Defect Analytics - Python natural language classification to develop transformation roadmaps
Test Optimization - Platform to identify test model minimization inputs
Knowledge - Platform to rank and retrieve client information via NL interface
Optimization before Automation
The accelerated AI for
Defect Prediction
Defect Classification
Defect Analysis
Delivery update and Insight
Standardized Methods
