Sauce AI for Insights launched to eliminate the time teams waste navigating dashboards and parsing raw data to understand what's happening across test pipelines. Log-diving is a tax on engineering time. Every failed job that requires manual investigation is a context switch that slows everything down.
Sauce AI for Insights now includes automated test diagnostics — a capability that provides job-level root cause analysis directly within the platform. When a job fails, skip the log files. Query Sauce AI for Insights with a job ID, and it automatically parses test execution data — commands, timestamps, error outputs, and failure sequences — then returns a structured diagnosis that includes:
Root cause classification: pinpoints whether the failure originated at the infrastructure, environment, or code level
Warning summaries: surfaces hidden issues and environmental flakes that could impact future runs
Smart fixes: tailored, actionable recommendations to get the test back to passing
No manual correlation. No context-switching into a separate debugging environment. Just ask:
"Why did this job fail [jobID]?"
"Tell me what went wrong with job [jobID]."
"Give me a forensic analysis of my last five failed jobs."
This release is optimized for Appium and Selenium use cases. Support for additional frameworks is on the roadmap for later this year. The agent's command library is also actively expanding so if it doesn't recognize a specific command yet, coverage updates are rolling out regularly.
Individual test-level debugging for batch frameworks is scoped as a future enhancement.
Manual log analysis is one of the highest-friction points in any test pipeline. This update eliminates that friction for the failure types engineers hit most without requiring new tooling or a workflow change. Faster RCA means fewer debug cycles, less time blocked on QA, and a cleaner path to release.
Automated test diagnostics is now available to all Sauce AI for Insights users.
Learn more about all the capabilities of Sauce AI for Insights.