AI is revolutionising software engineering, but how do you know when you can trust AI? Software quality engineering specialist Srikanth Kavuri uses machine learning (ML) and research into explainable AI to build more reliable pipelines for testing enterprise-scale systems. “Traditional enterprise systems were designed and deployed as siloed applications,” said Srikanth Kavuri, a software quality engineer and researcher specialising in explainable AI. Using predictive ML models, his research describes a system for scoring each component in an enterprise repository according to failure likelihood. In his presentation titled, “From Blackbox AI to Trustworthy Software Systems,” Kavuri shares how ML systems can be leveraged for predicting failures at scale.

Source: dna March 30, 2026 08:20 UTC