How DigyAI could help you
DigyAI is the artificial intelligence component of the Digy4 platform, designed to deliver advanced analytics and insights throughout the software testing lifecycle. By leveraging machine learning , multiple LLMs and other AI techniques, it automatically analyzes test data to identify patterns, root causes of failures, and flaky tests—helping teams gain deeper visibility into quality metrics. DigyAI also integrates with DigyDashboard to deliver real-time notifications and insights, enabling proactive decision-making and more efficient test processes. DigyAI drive efficiency by real-time AI driven insight and actioning adding significant efficient.
DigyAI - Insight AI
Turn Data to Intelligence
AI-Powered Root Cause Analysis (DigyRCA)
DigyRCA (Root Cause Analysis) is a feature within the Digy4 platform designed to help teams quickly identify and understand the underlying causes of test failures or quality issues. By analyzing logs, historical data, and test artifacts, DigyRCA pinpoints where problems originate—whether it’s code changes, environment factors, or flaky tests—so teams can efficiently address issues and maintain stable, reliable test suites.
- Reduce Mean Time to Resolve (MTTR) by up to 25%.
- Cut Mean Time to Detect (MTTD) by 60–80%
- Boost efficiency & accelerate troubleshooting
DigyAssist
DigyAssist is an AI Agent within the Digy4 ecosystem that helps teams interact with testing data and insights in real time. By integrating with popular communication channels, it can:
- Provide Updates & Alerts: Share execution statuses, test outcomes, and critical alerts directly in your chat tool.
- Answer Queries: Fetch specific metrics or historical data on demand (e.g., “What’s the latest pass rate for my team’s test suite?”).
- Suggest Actions: Offer recommendations, such as re-running failing tests or investigating flakiness, based on AI-driven analysis.
- Facilitate Collaboration: Streamline discussions around test results and release readiness by bringing actionable information right into the conversation.
Overall, DigyAssist acts as a centralized, interactive hub for quick insights and faster decision-making.
Flakiness Score in DigyAI
Flakiness Score in DigyAI refers to a metric that quantifies how often a test produces inconsistent outcomes—passing at times and failing at others—without any changes in the underlying code or environment. By analyzing historical execution data, DigyAI calculates a score that highlights the degree of unpredictability in a test’s results. Key points include:
- Historical Runs: DigyAI examines previous runs of a test case to see how frequently the outcome changes unexpectedly.
- Consistency Check: If a test flips between pass/fail states under the same conditions, it’s considered flaky.
- Scoring Logic: Flakiness is scored based on the ratio of inconsistent runs to total runs, often factoring in patterns such as consecutive failures or intermittent behavior.
- Actionable Insights: Once flagged, flaky tests can be prioritized for troubleshooting, stabilizing them and improving overall test suite reliability.
This Flakiness Score helps teams identify which tests need attention, reduces noise in results, and ensures more trustworthy pipelines.
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