t-Triage
AI-powered test failure triage and automation management for QA teams
About t-Triage
t-Triage is an agile test case management and automation failure analysis tool by Clarolab. It uses AI and machine learning to automatically classify test failures, distinguish real bugs from false positives and flaky tests, and set structured triage workflows for continuous delivery teams. Built from 15+ years of internal QA practice.
Pros & Cons
Pros
- Reduces manual triage effort with ML-based failure classification
- Automatically distinguishes real bugs from flaky or environment failures
- Deep integration with CI/CD and project management tools
- 15+ years of battle-tested QA development behind the product
- Promotes team accountability via test suite ownership assignment
Cons
- No public pricing — requires sales contact
- Relatively niche vendor with limited community presence
- Limited public documentation and user reviews
- Small company — may have limited support resources
Key Features
AI Failure Classification
Machine learning automatically classifies test failures with 60+ intelligent triage rules
Kanban Triage Workflow
Visual kanban board for managing daily triage lists and test failure backlogs
CI/CD Integration
Connects with Jenkins, Bamboo, CircleCI, and other CI/CD tools
Test Framework Support
Works with Selenium, Robot Framework, Cucumber, Protractor, and more
Issue Tracker Integration
Integrates with JIRA, Slack, Mantis, and Redmine for bug tracking
Big Data Analytics
Dashboard with team performance, test ownership, and productivity insights
Pricing
- AI failure classification
- Kanban triage
- CI/CD integration
- Test framework support
- Analytics dashboard
Best For
CI/CD Test Triage
Automatically triage automated test failures in continuous integration pipelines
Regression Suite Management
Manage large regression and smoke test suites across multiple products
Flaky Test Detection
Identify and classify flaky tests vs. real product bugs to reduce noise
QA Team Performance
Track QA team performance and test health metrics over time
