Ocean surface currents are routinely derived from satellite observations of the sea level, allowing regional- to global-scale synoptic monitoring. In order to overcome the theoretical and instrumental limits of this methodology, we exploit the synergy of multi-sensor satellite observations. We rely on deep learning, physics-informed algorithms to predict ocean currents from sea surface height and sea surface temperature observations. Results are validated by means of in situ measurements.