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Cognitive Testing

We have an AI based integrated enterprise testing platform, categorized by:

  • Artificial Intelligence/Machine Learning in Testing

    : Ready-to-use AI powered automated visual testing framework, easily adaptable ML driven test automation framework and AI powered automated test designing framework, which seeks to reduce test designing effort by up to 60%
  • Testing AI Applications

    : Proprietary 3-tier "Train, Test, and Label" testing methodology, and 3D assurance framework for testing convesational interfaces
  • Intelligent QA: Natural Language Processing (NLP) based intelligent test data analytics applications for defect prediction and test analytics
  • AI powered Automated Visual Testing Framework: Visual functional and UI automated testing of key digital testing aspects—multiple browsers, multiple devices, responsive design checks, and localization support

    Benefits

    • Return on test coverage, quality/process and cost
    • Shift left testing leading to better quality
  • ML-driven Test Automation Framework: Auto healing of automated tests, regression testing based learnings from earlier executions and auto detection & validation of typical anomalies – latency issues, JavaScript errors, broken links etc.

    Benefits

    • Spend up to 75% less time creating and maintaining end-to-end automated testing script
    • Increased speed to find and fix bugs
  • AI Powered Automated Test Designing Framework: Improve quality and coverage of testing in product engineering by generating test cases through business models

    Benefits:

    • Up to 60% test design effort reduction
    • Better coverage and quality leading to enhanced customer experience
  • 3-Tier "Train, Test, and Label" testing methodology: AI infusion in applications can be at different levels. Level one covers basic support applications using just NLP. Level two could be smarter applications with machine learning and analytical capabilities. Level three are intelligent applications with wide knowledge and deep learning capabilities. Testing methodology for these applications ought to be different. Our proprietary 3-Tier "Train, Test, and Label" testing methodology can be used with customization to test all the three different levels of AI infused applications.

    Benefits

    • Enhanced confidence in AI applications
    • Optimized testing with faster time-to-market
  • 3D Assurance Framework for testing conversational interfaces: Testing conversational interfaces such as chatbots require assurance for 3 dimensions, channel integration, conversational flow and monitoring. Our 3D Assurance framework includes test process and automated utilities / tools for high test coverage and speedy execution.

    Benefits

    • Up to 60% reduction in test data creation effort
    • Enhanced customer interaction leading to improved revenues
  • Software Defect Predictor: Predicts defects using AI with 80% accuracy based on changes, historical data, and production incidents

    Benefits:

    • Accelerated releases by optimized test planning
    • Shift left on high risk areas tested for product releases
  • Smart Test Analytics: Uses AI to automatically identify traceability between Requirements and Test Cases and Missing Test Cases

    Benefits

    • Accelerated product releases through targeted testing
    • Reduced rework

 

 

Cognitive Testing
Why Us ?
  • Train, Test, and Label methodology for testing AI/ML based Applications
  • Inhouse Visual AI integrated Digital ASE2T for testing web and mobile applications that reduces 80% of visual testing effort
  • Integrated test automation platform for testing conversational interfaces
  • Strategic partnership with AI/ML based tool vendors

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