Our goal isn't a one-off demo — it's a system the public and authorities can depend on. That means it must be production-grade, and built on a complete AI ecosystem.
Every weather station runs 24/7. A precise monitoring mechanism watches each station's health and flags any outage instantly — so no location ever loses coverage.
Add more stations across regions and the ecosystem keeps performing optimally — the same speed and accuracy whether it's a handful of stations or thousands.
10 → 10,000+ stationsAccurate predictions by fusing three AI models — sky-camera vision, sensor time-series and satellite/radar geospatial — instead of relying on one signal.
3-model fusionQuick response — readings are processed and warnings delivered within seconds, so alerts reach people while there's still time to act.
alerts in secondsThe entire ecosystem is resilient to cyber attacks. Every station and the cloud sit on a private VPN
Private VPN · zero-trustThe intelligence — Vision, Time-Series and Geospatial models that learn storm patterns and predict thunderstorms.
Vision · Time-Series · GeospatialThe operating system it all runs on — the most widely-used server OS, powering the cloud and the stations.
server OS foundationThe best hardware for the job — GPU servers (like our data-centre AI-HPC server) that train the models and run predictions fast.
GPU · AI-HPC serverThe production deployment method — package the app once and run it identically on any machine, from a laptop to the cloud.
build once · run anywhereWhere the workloads actually run — Edge / Cloud Computing: sensors at the edge, heavy AI in the cloud.
Edge + CloudProduction Grade makes it dependable — always on, accurate, fast and secure. The AI Ecosystem gives it the intelligence and the infrastructure. Together, that's a system the public and disaster authorities can rely on for real early warning, not just a demo.