Accelerated testing productivity & increased test coverage

Quality Engineering (QE) is undergoing a rapid transformation, shifting from traditional manual testing to AI-driven methodologies. Manual testing was once crucial for identifying bugs and validating functionality, it was often thorough but time-consuming, prone to errors, and unable to keep pace with the rapid development cycles of modern software. Infogain’s AI driven tools, platform, expertise, best practices, and accelerators enable you to deliver high quality through adoption of AI tools.

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Assessment &


Advisory


Roadmap to mature Intelligent Quality Engineering

Our assessment and Advisory services would assess the QE practices, tool, talent, and cultural aspects with appropriate building blocks that shall enable transformation of matured Quality Engineering organizations to achieve improved quality of software products, reducing risks, and customer satisfaction.

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CORE


QUALITY


ENINGEERING


Delivering digital experiences and speed to market

Traditional Functional and Non-Functional testing services are revolutionized through AI platform-based QE services. QE organizations are restructured with revised AI based roles (AI SDET’s) and AI tools across STLC. Our AI journey follows AI-Guided AI-Assisted  AI-Led QE services.

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Next Gen


QE Services


Digital Engineering Testing

Quality Engineering services that certify releases for Application modernization, Data & Analytics, AI Model Testing, Cloud migration Testing, Data Center Migration, ELT DW Testing, IoT Testing, Device Testing (Medical devices, Mobile app, Wearables etc..), ERP packaged applications, accessibility, and UX testing

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PAQman –


Infogain’s AI Enabled


QE Platform


Accelerating QE delivery through automation

Infogain has custom built QE platform that covers end-to-end QE services based on AI Led Productivity and AI Led Autonomous testing features across STLC stages. AI is leveraged for Test Case Generation, Test Script Generation, Test Data Generation, Performance Monitoring, Performance scripting, Load modelling, Defect Prediction, Failure Analysis, Self-Healing, Test Case Prioritization and Test Insights.

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