Understand Every Decision Your AI Makes

When ContextAI's AI creates or modifies a test step, it doesn't just execute — it explains every choice. You'll discover:

• Which element was selected and the reasoning behind the optimal match
• The complete decision path including visual, DOM, historical, and semantic signals
• Alternative paths evaluated and why they were rejected for better test reliability

When your application evolves and AI adapts your tests, our explainable AI testing provides:

• A comprehensive before-vs-after view of all impacted elements and steps
• Human-readable reasoning trails explaining how healing or replacement was performed
• Complete confidence knowing your tests adapt with intelligent context, not random guesswork

Every AI recommendation includes detailed scoring and explanations. Our transparent AI automation shows:

• Confidence scores calculated from multiple weighted signals and decision factors
• Visual indicators (high, medium, low) helping assess risk and manual review requirements
• Access to comprehensive AI logs for deep debugging and compliance documentation

Using advanced contextual mapping, our AI feature explanation links test steps directly to:

• Requirements and user stories for complete project alignment
• Application workflows ensuring comprehensive coverage
• Mind map nodes when using visual planning methodologies

With every test execution and user interaction, our AI learns and improves while showing you exactly how:

• Understand precisely what the system learned and why behavior was adjusted
• View flagged patterns, anomalies, and identified improvement opportunities
• Receive test quality insights directly connected to AI model behavior and decisions