When snow falls, the landscape transforms into a sparkling white marvel. Beyond its beauty, snow is essential to human sustenance across large regions: it replenishes drinking water supplies, moderates our planet's temperature, drives hydropower production, and feeds irrigation systems. Yet snow also brings hazards. Avalanches pose a persistent threat in mountainous terrain, rapid snowmelt combined with heavy rainfall can trigger devastating floods, and intense snowfall events regularly disrupt road and air traffic at considerable economic cost. Preparing effectively for such events demands reliable forecasts of snow conditions. In Switzerland, where a substantial fraction of precipitation falls as snow, the WSL Institute for Snow and Avalanche Research (SLF) provides such forecasts using a physics-based snow modelling system recently implemented in the Julia programming language. These forecasts support avalanche and flood forecasting as well as weather-related hazard alerts. Our model is also used across a range of research projects, including efforts to improve inflow forecasts for Norwegian hydropower reservoirs and to better characterize snow dynamics on glaciers in high-mountain regions. Here, we present a brief overview of the operational use cases of this newly developed system alongside its research applications, together with a more detailed account of our technical implementation and the challenges encountered so far. We welcome feedback on our technical implementation and are eager to explore potential collaborations in which the model could be coupled with other Earth system models.