Gen AI based Auto Code Generator
AI based model to detect changes
AI based auto detection Of UI Changes
Anomaly Detector
Gen AI Pcloudy Action Bot
Pcloudy employs a human-in-the-loop approach, integrating human reviewers to validate outputs and provide feedback, ensuring high standards of accuracy and continuous improvement in AI models.
Pcloudy ensures data security and privacy by not using customer data for AI training without explicit consent. Data is sent to secure, compliant servers and protected with advanced encryption. All processes comply with GDPR and other data protection laws.
Pcloudy ensures ethical AI use by conducting continuous ethics reviews to eliminate biases and harmful outputs. AI impact assessments are mandatory before deployment, and governance processes track AI algorithms and label datasets to ensure accountability and fairness from the start.
Pcloudy's AI models feature built-in explainability for transparency, provide clear disclosures on data and AI usage, and maintain robust feedback mechanisms to report AI practice concerns, ensuring continuous improvement and ethical alignment.
Pcloudy's AI Governance Board ensures regulatory compliance, ethical standards, and infrastructure security. Post-deployment remediation processes address any negative AI impacts promptly. Mandatory AI ethics training for engineers and product managers embeds ethical considerations throughout AI development.
Pcloudy's AI-powered testing agents provide comprehensive coverage across every testing stage, from autonomous test creation to intelligent analytics. The platform uses multiple AI testing techniques including QPilot, QHeal, QLens, and QObserve to handle your entire testing lifecycle automation.
QPilot, Pcloudy's AI test automation tool, functions like a human test automation engineer. It uses intelligent automation to create test scripts from natural language descriptions, enabling less technical testers to automate complex applications with its AI-powered test generation capabilities.
QHeal is an AI-based test maintenance solution that automatically adapts to UI changes. This intelligent test healing mechanism identifies alternative selectors and positioning strategies, reducing test maintenance efforts by automatically fixing broken test scripts through AI-driven test repair.
QLens uses Visual AI to automatically detect visual defects across devices and screen sizes. This intelligent visual testing tool captures screenshots and compares them against baselines, using AI-powered visual verification to identify significant visual inconsistencies while ignoring minor rendering issues.
QObserve provides AI-powered test analytics and real-time automated anomaly detection. This intelligent monitoring system delivers immediate insights on test executions, offering proactive alerts on critical failures and enhancing team collaboration through AI-driven test insights.