Streamline your Tricentis qTest log investigation with AI
Swiftask turns complex test logs into actionable diagnostics. Identify root causes in seconds instead of hours.
Result:
Cut debugging time and accelerate your software delivery cycles.
AI Agents
tricentis qtest
Connector tricentis qtest · Secure OAuth 2.0
The bottleneck of manual log analysis
QA teams spend an excessive amount of time sifting through thousands of lines of logs generated by Tricentis qTest after every run. This tedious task slows down fixes and delays production releases.
Main negative impacts:
Excessive debugging time
Manual log analysis consumes precious hours that your engineers could be spending on development.
Cognitive fatigue and errors
Repeatedly reading complex logs increases the risk of missing the real root cause of a bug.
Slowed CI/CD cycles
Unresolved failures block deployment pipelines, directly impacting engineering team velocity.
Swiftask automates the investigation. Our AI agent ingests Tricentis qTest logs, correlates errors with previous runs, and provides a clear summary of the root cause.
BEFORE / AFTER
What changes with Swiftask
Traditional analysis process
A test fails in qTest. A QA engineer downloads logs, opens them in an editor, searches for keywords, and manually compares with past runs. A laborious search that can take all afternoon.
AI-augmented investigation with Swiftask
As soon as a failure is detected, Swiftask analyzes the logs instantly. You receive an intelligent summary explaining why the test failed, with a link to the critical code or infrastructure section.
Automate your QA diagnostic in 4 steps
1
STEP 1 : Connect your qTest instances
Link Swiftask to your Tricentis qTest environment via our secure connectors to automatically import execution logs.
2
STEP 2 : Set analysis rules
Configure the criticality criteria and error types the agent should prioritize when monitoring your logs.
3
STEP 3 : AI investigation launch
Swiftask scans logs in real time during every test failure and performs semantic correlation with your known bug databases.
4
STEP 4 : Access diagnostic report
Receive a notification with the full diagnostic, ready to be shared with developers for immediate resolution.
Capabilities of your AI agent
The agent examines stack traces, system error messages, configuration changes, and network context associated with qTest runs.
- Target connector: The agent performs the right actions in tricentis qtest based on event context.
- Automated actions: Automatic regression identification. Error classification (infra vs code). Natural language log summary. Automatic notifications on Slack/Teams/Jira.
- Native governance: The agent learns from your past resolutions to improve the accuracy of future diagnostics.
Each action is contextualized and executed automatically at the right time.
Each Swiftask agent uses a dedicated identity (e.g. agent-tricentis-qtest@swiftask.ai ). You keep full visibility on every action and every sent message.
Key takeaway: The agent automates repetitive decisions and leaves high-value actions to your teams.
Why choose Swiftask for your logs
Reduced MTTR
Mean Time To Repair is cut by 5x thanks to instant root cause identification.
Focus on high-value work
Your QA experts focus on creating tests rather than repetitive log analysis.
Improved software quality
A better understanding of failures leads to deeper and more effective bug fixes.
Seamless integration
Works in the background without changing your existing testing processes in qTest.
Data governance
Your logs remain secure with strict access control and industry-standard compliance.
Security and compliance
Swiftask applies enterprise-grade security standards for your tricentis qtest automations.
- Data encryption: All logs transiting between qTest and Swiftask are encrypted in transit and at rest.
- Enterprise compliance: Solutions designed for regulated environments with log management compliant with GDPR.
- Environment isolation: Each client has their own isolated instance to ensure test data confidentiality.
- Full audit trail: Keep a record of all analyses performed by the AI for your compliance reports.
To learn more about compliance, visit the Swiftask governance page for detailed security architecture information.
RESULTS
Measurable operational impact
| Metric | Before | After |
|---|---|---|
| Average investigation time | 60-120 minutes | Under 5 minutes |
| Bug resolution rate | Variable | 40% increase in velocity |
| Manual analysis | Daily | Zero |
| Diagnostic accuracy | Human (prone to error) | AI (consistent and audited) |
Take action with tricentis qtest
Cut debugging time and accelerate your software delivery cycles.