Artificial Intelligence (AI) and Machine Learning (ML) in particular are finding widespread applications in many industries. However, many customers across industry verticals, contemplating the adoption of ML in their business and IT process automation, have unreasonable expectations about the capabilities of these learning machines. Many imagine or opine that ML can completely take over human tasks. We will take a closer look at ML, explain the learning process and set the right expectations for these customers.

Using machine learning and analytics, Pranitec helps unlock the power of data (like project documentation, test artifacts, defect logs, test results, production incidents, etc.) and drives automation and innovation, improving QA efficiencies beyond the reach of traditional QA practices.

Infosys AI/ML-led QA offering, based on a scientific approach using both supervised and unsupervised methods, helps unearth defects beforehand, optimize testing and predict failure points, thus reducing the overall cost and achieving high customer satisfaction.

Our approach to artificial intelligence (AI) / machine learning (ML) based quality assurance is design-based, complying with the following steps – Discover > Learn > Sense > Respond cycle. The knowledge base constantly helps in storing and building pattern, which in turn helps in self-learning and responding to actions.