Pricing

Supercharge your QA strategy: AI-driven Qase trend analysis

Swiftask connects your Qase test data to AI agents to analyze trends in real-time. Stop reacting to regressions, start predicting them.

Result:

Turn raw test data into strategic decisions and dramatically reduce your time-to-market.

Manual test analysis slows down your release cycles

Your QA teams spend hours compiling reports in Qase without ever truly identifying the root cause of instabilities. Data piles up, but hidden trends—like code fragility or flaky tests—remain invisible until the next major incident.

Main negative impacts:

Delayed regression detection: Without automated analysis, failure patterns are only identified once the bug hits production.
QA cognitive overload: Manual test result analysis is time-consuming and prone to human error, preventing QA from focusing on test improvement.
Lack of strategic visibility: It's difficult to communicate overall quality to stakeholders without AI-based synthetic reporting.

Swiftask automates the analysis of your Qase data. Our AI agents scan your test history, correlate results, and proactively alert you to critical trends.

BEFORE / AFTER

What changes with Swiftask

Standard Qase Analysis

A QA engineer downloads reports, tries to manually correlate test failures over several days, and guesses which modules are unstable. The process is slow and lacks precision.

Augmented analysis with Swiftask

Your AI agent monitoring Qase automatically detects a 15% increase in failures on a specific module. It sends a contextual summary to your communication tool, suggesting an investigation into the latest deployment.

Deploy your QA analysis agent in 4 steps

STEP 1 : Swiftask-Qase API Connection

Link your Qase instance to Swiftask in a few clicks via a secure API key to enable test data ingestion.

STEP 2 : Indicator Configuration

Define the test KPIs to monitor (success rate, duration, flakiness) that the AI should prioritize.

STEP 3 : Alert Parameterization

Configure trigger thresholds to receive intelligent notifications on your preferred channels.

STEP 4 : Continuous Automated Analysis

Your agent analyzes every test execution and generates actionable insights without intervention.

Advanced AI analysis features

The agent examines failure frequency, correlation with new versions, and flaky test history to isolate root causes.

Target connector: The agent performs the right actions in qase based on event context.
Automated actions: Automatic 'flaky' test detection. Weekly quality trend synthesis. Immediate alerts on critical regressions. Prediction of high-risk code areas.
Native governance: All analyses are stored in Swiftask to build a historical knowledge base on your product quality.

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.

Why automate your test analysis

1. Faster debugging

Identify root causes faster thanks to AI-automated correlations.

2. Improved reliability

Proactively eliminate flaky tests that pollute your QA results.

3. Total transparency

Clear and actionable reports for both technical teams and management.

4. Focus on high-value work

Free your QA engineers from repetitive analysis tasks.

5. DevOps alignment

Integrate quality into the heart of your CI/CD pipeline with real-time insights.

Test data security

Swiftask applies enterprise-grade security standards for your qase automations.

Data encryption: All data extracted from Qase is encrypted in transit and at rest.
Limited access: The agent only has access to the data necessary for analysis, based on your permissions.
Compliance: Architecture designed to meet the strictest B2B SaaS security standards.
Auditability: Every analysis performed by the agent is traceable in your Swiftask history.

To learn more about compliance, visit the Swiftask governance page for detailed security architecture information.

RESULTS

Impact on your QA productivity

Metric	Before	After
Failure analysis time	Several hours per week	A few minutes (AI summary)
Production bug rate	High (late detection)	Significant reduction
QA visibility	Data siloed in Qase	Centralized and proactive insights
Flaky test management	Manual and neglected	Fully automated

Take action with qase

Turn raw test data into strategic decisions and dramatically reduce your time-to-market.