Infogain: A Case study in Predictive, AI-driven Automation
Intelligent Automation is no longer a nice to have in today’s IT world. The market demands responsiveness and responsiveness mandates speed and flexibility. Vast teams of manual testers no longer fit this new paradigm. The most mature, value-focused IT organizations will find a way to prevail. One approach to the problem hinges on the innovative idea of utilizing open source tools to build an advanced testing framework integrated with a predictive analytics capability. The resulting solution dubbed a ‘Continuous Quality Engine’ at Infogain, enables a process of optimized test planning based on predicted points of failure, the execution of an optimized automated test suite, the assessment of the results and the machine learning-driven improvement of our prediction algorithms. The full automation of quality assurance processes is no longer the stuff of science fiction. Solutions like Infogain’s Continuous Quality Engine are opening a door to this new paradigm in software development and once companies begin to step through it, there will be no looking back.