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ABSTRACT Detecting offshore earthquakes in real time is challenging for traditional land-based seismic networks due to insufficient station coverage. Application of distributed acoustic sensing (DAS) to submarine cables has the potential to extend the reach of seismic networks and thereby improve real-time earthquake detection and earthquake early warning (EEW). We present a complete workflow of a modified point-source EEW algorithm, which includes a machine-learning-based model for P- and S-wave phase picking, a grid-search location method, and a locally calibrated empirical magnitude estimation equation. Examples are shown with offshore earthquakes from the SeaFOAM DAS project using a 52-km-long submarine cable in Monterey Bay, California, demonstrating the robustness of the proposed workflow. When comparing to the current onshore network, we can expect up to 6 s additional warning time for earthquakes in the offshore San Gregorio fault zone, representing a substantial improvement to the existing ShakeAlert EEW system.