AI RESEARCH
TingIS: Real-time Risk Event Discovery from Noisy Customer Incidents at Enterprise Scale
arXiv CS.LG
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ArXi:2604.21889v1 Announce Type: cross Real-time detection and mitigation of technical anomalies are critical for large-scale cloud-native services, where even minutes of downtime can result in massive financial losses and diminished user trust. While customer incidents serve as a vital signal for discovering risks missed by monitoring, extracting actionable intelligence from this data remains challenging due to extreme noise, high throughput, and semantic complexity of diverse business lines.