Presented ML-based anomaly detection and SLA prediction systems to senior stakeholders at DXC. Built using XGBoost and Random Forest — the SLA prediction model achieved 0.1% variance in forecast accuracy. Currently under patent review as a first-of-kind application of predictive ML in backup operations.