While leveraging AI for testing apps for quality, enterprises may face multiple challenges such as identifying the exact use cases, lack of awareness about what really needs to be done, verifying the app behavior based on the data that has been input, testing apps for functionality, performance, scalability, security, & more. AMZ Softtech’s extensive experience in the use of AI, ML, & analytics helps enterprises improve their automation frameworks & QA practices. AMZ Softtech provides AI/ML-led testing and performance engineering services for your QA framework through implementation of its next gen IP.

• Defect Analytics
  • Use of AI-based Sentiment Analytics:  Analyzer (CESA) – AI-tool to find, categorize, and distribute the overall sentiment of a conversation (Positive, Negative, Neutral) for better decision making
  • Realtime Dashboard & AI-based Predictive Analytics: Analytics-driven workload modelling for defect prediction, code coverage, response time, & scalability prediction
• Performance Engineering approach
  • ML-based analytics driven Performance Predictions: Workload modeling & response times
• Regression Optimization
  • Automated collation of the dependent test cases/scripts-based on the changes: Cigniti Impact Analyzer – solution for test suite impact analysis during Change Requests, Patches, & upgrades
  • Automated prioritization of test cases/scripts-based on Machine learning
• Smart Automation
  • Automated change detection in the object properties across scripts for every new release
  • Self-healing of test scripts based on the application changes