What Is an AI Maturity Model?
A maturity model is a framework used to assess how well your organization uses a
Building a Modern Mobile and Web Application with Robust CI/CD Automation and AI-Powered Multi-Device Testing
A leading start-up in the online consulting platform domain, this company focuses on connecting end-users with top industry professionals for expert consultation services. Known for its innovative approach and cutting-edge technology, the company aims to provide seamless and efficient solutions for both consultants and clients, ensuring high-quality interactions and problem-solving experiences. Applied AI Consulting has created the modern stack with payment gateway integration for this customer. This case study is focused on quality engineering.
Cross-Platform Compatibility: Building a modern application that supports both mobile and web platforms can introduce challenges in ensuring consistent functionality and user experience.
Testing Coverage: Ensuring thorough and reliable UI and API testing to cover all possible use cases and scenarios, which is crucial for maintaining application quality and reliability.
Automation Integration: Integrating automation testing into the CI/CD pipeline effectively, ensuring that automated tests run seamlessly with each deployment to catch issues early.
Performance and Reliability: Maintaining high performance and reliability of the application across multiple platforms and under varying load conditions.
A maturity model is a framework used to assess how well your organization uses a
Applied AI Consulting is proud to announce a strategic partnership with Nisum, aimed at delivering
Developed and Integrated Automation Frameworks: Created a Selenium-Python-based framework for UI testing and a pyTest framework for API testing, integrating them with the CI/CD pipeline.
Executed Cross-Platform Testing: Utilized aiTest for automation across multiple devices, browsers, and versions, including API quality validation with Postman collections.
Enhanced Communication and Visibility: Provided test execution updates and analytics through Slack and email, and demonstrated automation results in end-of-iteration demos.
Achieved very high application quality with minimal defects and ensured a seamless user experience across devices and browsers.
Reduced testing time by 40% through CI/CD integration and automation, leading to faster feature releases and updates.
Decreased testing-related costs by 30% and improved application performance, contributing to higher user retention and scalable growth.
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