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Endigest AI Core Summary
This article describes how GitHub built an AI-powered, event-driven workflow to systematically capture, triage, and act on accessibility feedback at scale.
•Accessibility issues previously lacked clear ownership, causing feedback to scatter across backlogs and bugs to linger without resolution
•GitHub built an internal workflow using GitHub Actions, GitHub Copilot, and GitHub Models API to ensure every accessibility report becomes a tracked, prioritized issue
•The system uses stored prompts instead of model fine-tuning, allowing accessibility experts to update AI behavior via pull requests without retraining
•GitHub Copilot automatically populates ~80% of issue metadata including WCAG violation classification, severity level (sev1–sev4), affected user groups, and recommended team assignments
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90% of feedback flows through GitHub's public accessibility discussion board, where community context enriches reports before internal tracking begins
This summary was automatically generated by AI based on the original article and may not be fully accurate.
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