AI/ML Testing

Preparing for a future of intelligence and productivity.

Qapitol QA > AI/ML Testing

Emerging Tech Testing


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Eliminate
Test Cases Redundancy

Save up to one third of your time by identifying and eliminating test case redundancies. Apply artificial intelligence and machine learning techniques to improve testing productivity.

Prioritize
Regressions

Prevent regression failures by accurately identifying and resolving defective components. Get insights into probable errors and problem areas through intelligent analytics.

Highlight
Missing Requirements

Ensure better coverage and identify defects early. Save time and manual effort by auto-mapping of requirements with test cases. Explore the tools that can make automation easy to implement and quick to learn.

Predict
Potential Failures

Mine test scenarios and execute appropriate test cases based on potential application failure areas. Detect high risk areas and decide the right test cases to be executed.

Perform
Impact Analysis

Get a graphical view of the component interactions without the need for programming techniques. Visual engineering and testing makes it accurate and actionable when it comes to defect management.

Sentiment
Analysis

Analyze user reactions efficiently by collating feedback and automatically analyzing positive comments and negative signals. Early analysis means quick resolutions.

By 2021, intelligent automation will generate an additional 20% savings over what is achievable today in application testing services for end users. “

Gartner

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