Analyze your Qase test coverage with AI
Swiftask connects your AI agents to Qase to audit your test coverage continuously. Identify flaws in your QA strategy instantly.
Result:
Turn your test data into actionable insights. Improve the quality of your software releases in record time.
AI Agents
qase
Connector qase · Secure OAuth 2.0
The complexity of measuring QA coverage
Maintaining accurate visibility over test coverage in Qase becomes impossible as your project grows. Teams waste valuable time cross-referencing data manually, often leaving critical areas untested.
Main negative impacts:
Invisible coverage gaps
Critical features remain without associated tests, creating risks of costly regressions in production.
Inefficient manual analysis
Manual auditing of test plans is slow, error-prone, and cannot react to code changes in real time.
Strategic misalignment
Without a clear view of actual coverage, QA efforts are poorly directed toward areas already saturated with tests.
Swiftask automates the analysis of your Qase coverage. Our AI agents crawl your test cases, compare results against requirements, and alert you on areas that need coverage.
BEFORE / AFTER
What changes with Swiftask
Without Swiftask
A QA lead spends hours generating Excel reports to check which modules are covered. Decisions are made on stale data, and omissions are discovered too late, often after deployment.
With Swiftask + Qase
As soon as an update is detected in Qase, your AI agent analyzes coverage. You receive an intelligent report identifying exactly which tests are missing before the test cycle even begins.
Optimize your Qase coverage in 4 steps
1
STEP 1 : Link your Qase project
Connect your Qase instance to Swiftask in a few clicks to give your AI agent access to your test data.
2
STEP 2 : Define your test priorities
Teach the agent what constitutes 'full' coverage for your critical modules.
3
STEP 3 : Run automatic analysis
The AI agent processes Qase data and automatically detects gaps between requirements and existing tests.
4
STEP 4 : Get actionable recommendations
Get precise suggestions on new test cases to write to secure your application.
AI analysis capabilities for Qase
The AI evaluates density, priority, and relevance of tests against recent code changes.
- Target connector: The agent performs the right actions in qase based on event context.
- Automated actions: Risk area identification, automated coverage reporting, QA task prioritization, alerts on potential regressions.
- Native governance: All analyses are logged in Swiftask to track the evolution of your QA maturity over time.
Each action is contextualized and executed automatically at the right time.
Each Swiftask agent uses a dedicated identity (e.g. agent-qase@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.
Benefits for your QA team
Drastic risk reduction
Detect uncovered areas before they become bugs in production.
10x Productivity
Free your QA engineers from tedious audit tasks through automation.
Data-driven decisions
Drive your testing strategy with precise and objective metrics.
Rapid alignment
Ensure every product evolution is immediately accounted for in Qase.
Seamless integration
Work directly in Qase, Swiftask handles the intelligence in the background.
Test data security
Swiftask applies enterprise-grade security standards for your qase automations.
- Secure API connection: The integration follows Qase security standards for protected reading of your data.
- Guaranteed privacy: Your test data is never used to train public models.
- Granular control: Manage access and analysis scopes for the AI from your Swiftask dashboard.
- Compliance assured: The audit trail helps justify test coverage for ISO or regulatory standards.
To learn more about compliance, visit the Swiftask governance page for detailed security architecture information.
RESULTS
Impact on your QA performance
| Metric | Before | After |
|---|---|---|
| Coverage audit time | Several days per sprint | Minutes in continuous mode |
| Detection of test omissions | During manual testing | During planning phase |
| Confidence in deployments | Uncertain | Measurable and high |
| Cost of poor quality | High (prod bugs) | Significantly reduced |
Take action with qase
Turn your test data into actionable insights. Improve the quality of your software releases in record time.