MPHASIS COGNITIVE QUALITY ENGINEERING
AI platform for Quality Engineering
Product teams often struggle to balance between release frequency and defect leakage. The trade-off is difficult to manage for teams involved in testing of products with many possible configurations, products with third-party dependency, products that need specific equipment and lab set-up, and hardware products. While almost every organization wants to achieve 100% test automation, not all product teams within the enterprise can achieve that due to inherent nature of the products. To improve the quality of the testing and optimize beyond test automation, it is useful to use historical data to bring in the power of Artificial Intelligence and Machine Learning (AI/ML).
Mphasis Cognitive Quality Engineering (CQE) is an AI/ML platform that helps enterprises achieve improved quality, accelerated time-to-market, and cost optimization by prescribing decisive actions throughout testing life cycle. CQE can be utilized by product engineering teams and enterprises with large pool of applications with high interdependencies.
With the defect-prediction based test prioritization CQE models, engineering teams are aware about likelihood of failure of test cases at the start of the sprint. This helps to fix any bugs faster or avoiding them altogether without over-burning the team and abandoning story points. Mphasis CQE platform integrates easily with industry wide testing and software management tools such as Jira, ALM, and Test Rail.