Description
QMetry is a test management platform, owned by SmartBear, built to help QA and engineering teams create, organize, and run software tests, primarily inside Jira (as QMetry Test Management for Jira, or QTM4J) and Azure DevOps. It is marketed as an alternative to tools like TestRail for teams that want to scale testing without a proportional increase in manual effort.
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Test cases live alongside a team's existing Jira or Azure DevOps issues, with native support for BDD-style test authoring so tests fit into an existing CI/CD pipeline rather than a separate system. QMetry integrates with automation frameworks, version control systems, device clouds, and CI/CD tools like Jenkins, CircleCI, and Bitbucket, and it can be deployed on the cloud or hosted locally in the EU for teams with data-residency requirements.
QMetry's AI features center on reducing manual test-management work. AI-driven test authoring generates test cases directly from user stories, requirements, and acceptance criteria. Flaky test detection identifies unstable tests so teams stop chasing false failures, while AI-powered defect detection and triage connects failed tests to past defects, groups related issues, and surfaces likely root causes. Smart test suite optimization prioritizes which tests to run based on recent code changes, risk, and past failure history, so teams can skip redundant tests and focus on higher-risk areas. An intelligent search feature lets users query test cases, defects, and other artifacts using natural language instead of manual filters.
QMetry is built for QA and DevOps teams working in Jira or Azure DevOps environments, from small teams up through enterprise organizations; SmartBear states it supports 10 to 10,000-plus users without performance loss, and it includes an eSignature module aligned with 21 CFR Part 11 for regulated industries that need audited test approvals.
SmartBear does not publish self-serve pricing for QMetry on the product page; interested teams start a 14-day free trial or request pricing directly, and its dashboards and reporting are built around Jira and Azure DevOps workflows rather than as a fully stand-alone system.
- CategoryAI Code Review & Testing
- Pricing ModelNot specified
- DeploymentCloud
- PlatformsJira Cloud
QMetry's Core Features
AI-driven test authoring that generates test cases from user stories and requirements
Flaky test detection to identify unstable tests before they waste team time
AI-powered defect detection and triage linking failed tests to past defects and root causes
Smart test suite optimization that prioritizes tests by code change, risk, and failure history
Natural-language search across test cases, defects, and other testing artifacts
Native BDD support and integration with CI/CD tools like Jenkins, CircleCI, and Bitbucket
eSignature module aligned with 21 CFR Part 11 for regulated-industry approval workflows
Cloud or EU-hosted deployment options for data-residency requirements
How to use QMetry?
Connect QMetry to Jira or Azure DevOps: install QMetry Test Management alongside your existing issue tracker
Generate test cases: use AI-driven test authoring to draft cases from user stories and acceptance criteria
Run tests in your pipeline: integrate with CI/CD tools and automation frameworks to execute tests automatically
Triage failures: let AI-powered defect detection group related failures and flag flaky tests
Prioritize the next run: use smart test suite optimization to focus on high-risk, recently changed areas
Track results: review dashboards and reports on test execution, defects, and traceability
QMetry's Use Cases
- Test case generation
- Flaky test triage
- CI/CD test management
- Regulated test approvals
