Calsoft introduced an AI-powered approach to Test Impact Analysis that eliminates unnecessary test executions in CI/CD ...

Combine AI-generated tests with intelligent test selection to manage large regression suites and speed up feedback ...

Real-world deployments show 40% test cycle efficiency improvement, 50% faster regression testing, and 36% infrastructure cost savings.

QA teams now use machine learning to analyze past test data and code changes to predict which tests will fail before they run. The technology examines patterns from previous test runs, code commits, ...

As enterprises rethink their testing strategies, many teams are reviewing AI test automation tools that can help modernize QA workflows while keeping up with aggressive release schedules. These tools ...

Identify sources of unnecessary cognitive load and apply strategies to focus on meaningful analysis and exploration.

Modern software teams are expected to ship faster every quarter. At the same time, the systems they ship become more complex, more distributed and more regulated. As systems scale from monoliths to ...