Wildfires are a growing environmental and socio-economic threat driven by climate change and land abandonment. As fire frequency and intensity increase, suppression alone is no longer sufficient, making prevention and preparedness essential. Earth Observation and Geographic Information Systems (GIS) enable the integration of environmental and socio-economic factors into decision-support tools for wildfire risk assessment. This work presents a modular, web-based platform that computes a Wildfire Risk Index (WRI) through multi-criteria analysis and the Analytic Hierarchy Process (AHP). Two complementary risk formulations are developed for Galicia, northwestern Spain: a Static WRI, aimed at characterising baseline wildfire predisposition and supporting long-term prevention planning, and a Dynamic WRI, which incorporates short-term changes in vegetation and meteorological conditions to support operational preparedness. The Static WRI prioritises socio-economic factors (43.6%), while the Dynamic WRI gives greater weight to vegetation (45.6%) and meteorology (30.3%). The resulting maps show distinct spatial risk distributions, reflecting their different purposes. Validation of the dynamic model against MODIS active-fire detections yielded AUC-ROC values between 0.4935 and 0.8333, with six of eight validation periods exceeding 0.5. Both indices are integrated into a cloud-based Wildfire App, enabling automated risk calculation, visualisation, and updating through an interactive GIS dashboard. The results demonstrate the potential of combining static and dynamic WRI approaches to support complementary wildfire prevention and preparedness decisions.