Seismic records can provide detailed insight into the mechanisms of gravitational mass movements. Catastrophic events that generate long-period seismic radiation have been studied in detail, and monitoring systems have been developed for applications on very local scale. Here we demonstrate that similar techniques can also be applied to regional seismic networks which show great potential for real-time and large-scale monitoring and analysis of rockslide activity. This manuscript studies 21 moderate-size to large rockslides in the Eastern Alps that were recorded by regional seismic networks within distances of few tens of kilometers to more than 200 km. We develop a simple and fully automatic processing chain that detects, locates, and classifies rockslides based on vertical-component seismic records. We show that a kurtosis-based onset picker is suitable to detect the very emergent onsets of rockslide signals, and to locate the rockslides within a few kilometers from the true origin, using a grid search and a 1D seismic velocity model. Automatic discrimination between rockslides and local earthquakes is possible by a combination of characteristic parameters extracted from the seismic records, such as kurtosis or maximum-to-mean amplitude ratios. We attempt to relate the amplitude of the seismic records with the documented rockslide volume and reveal a potential power-law in agreement with earlier studies. Since our approach is based on simplified methods we suggest and discuss how each step of the automatic processing could be expanded and improved to achieve more detailed results in the future.