When an application is changed or updated by a developer, some of its functionality can falter during software testing in IBM. In my experience, while application development takes roughly 60 percent of a developer’s time, maintenance often takes up the other 40 percent.

This can become a major challenge for companies: developers should be able to focus on what they do best – creating innovative software – instead of spending a significant amount of their time on maintenance.

This problem inspired me to launch ContextQA, a low code/no code test automation platform that automates web and mobile application testing processes with AI.

By infusing automation into the development process, we are able to help developers efficiently identify and address software issues like robustness and flakiness, which often hinder businesses from releasing new features at speed and with high quality.

Today, I’m excited to share that we embedded IBM watsonx.ai into ContextQA to help streamline the software testing process for developers.

Collaborating with IBM helped us train our AI models with limited data, and in turn, we believe that we'll be better positioned to help developer teams more efficiently test an API, mobile application, or web application.

How IBM Watsonx.ai supports ContextQA with scaling AI and Automation in DevOps and AIOps    

Previously, automating one test case could take up to 8 hours and require a high knowledge of programming with specific testing frameworks in place. 

Working with IBM has enabled the ContextQA platform to use AI to help migrate these manual test cases into automated tasks. By using watsonx.ai models, we are able to address automation testing challenges like flakiness and auto-healing while providing developers with a seamless user experience as they test for bugs and UI best practices.

Additionally, our platform can help developers identify API changes and recalibrate test cases for consistency and accuracy to help enhance software quality.

Book a Demo and experience ContextQA testing platform in action with a complimentary, no-obligation session tailored to your business needs.

Why working with IBM helps ContextQA’s AI strategy

Since we are developing solutions for enterprise customers, it’s crucial for us to have a secured and trustworthy machine learning model that allows businesses and developers to not worry about the data.

After exploring several AI providers and learning about their limitations around aspects like the number of models we could use and potential privacy issues, we chose to work with IBM.

And, because IBM watsonx offers ready-to-use AI models, we were able to easily integrate IBM watsonx APIs into the ContextQA platform.

Our relationship with IBM has accelerated ContextQA's ability to provide AI-fueled solutions to enterprise clients in industries such as financial services, e-commerce and CX that are in need of a DevOps transformation.

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