![Chennam S.](/assets/transparent-ad5be28fbcd25b7b08d2cebe1d957125437fb5407d75ee717965ad22c8808791.gif "Chennam S.")
CS

Chennam S.

Head Of Quality Assurance

Small-Business (50 or fewer emp.)

8/21/2026

"Fast, Scalable Natural-Language Automation for End-to-End Regression"

5/5

What do you like best about testRigor?

What I like most about testRigor is that it allows us to automate end-to-end business workflows using natural language, without heavy dependency on coding or maintaining complex locators. It helps our QA team build and maintain regression coverage faster, especially for critical customer journeys. I also like its ability to run large regression suites in parallel, which gives us faster release confidence. For our team, the biggest value is reducing manual regression effort while allowing QA engineers to focus more on exploratory, risk-based, and new-feature testing. Review collected by and hosted on G2.com.

What do you dislike about testRigor?

The main challenge I see with testRigor is that some complex or highly customized workflows can still require additional effort to create, debug, and maintain. While natural-language automation makes script creation easier, troubleshooting failed tests can sometimes take time to identify whether the issue is with the application, test data, timing, or the test itself. Also, as the automation suite grows, maintaining test stability and execution time becomes increasingly important. Review collected by and hosted on G2.com.

What problems is testRigor solving and how is that benefiting you?

testRigor is solving the challenge of automating and maintaining large-scale end-to-end regression testing without creating a heavy dependency on traditional coding-based automation. In our QA process, we use it to automate critical business workflows and run around 450 regression workflows across multiple servers. This helps us reduce manual regression effort, improve regression coverage, and get faster feedback before staging and production releases. It also allows our QA engineers to spend more time on new-feature validation, exploratory testing, and risk-based testing instead of repeatedly executing the same regression scenarios. Review collected by and hosted on G2.com.

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