Atmo AI

Atmo AI

Forecast the weather more accurately, act faster.

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Description

This artificial intelligence enables optimizing weather forecasts by using data from satellites, radars, and other measurement stations, processed almost instantaneously by AI models. Atmo AI significantly improves forecast accuracy, offering up to 50% more accuracy over traditional models for time scales up to 14 days. In addition to providing microclimate-scale forecasts with a granularity reaching 1km², this tool is of great help for governments, businesses and meteorological organizations in proactive management of climatic phenomena. Des prévisions rapides et de haute résolution permettent ainsi de mieux anticiper et réagir face à l'évolution rapide des conditions météorologiques. Atmo AI is recognized for its ability to offer reliable and tailor-made solutions, indispensable in demanding and varied environments. It is the ideal tool for those who require a high level of precision and speed in weather forecasting.

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Who is using this AI?

Features

Real-time global meteorological data

This system collects in real time meteorological data via a broad network of satellites, ground stations, radars and ocean buoys. The use of artificial intelligence models allows continually refining forecasts, thereby strengthening their reliability and accuracy for practical application in sectors as critical as transportation or agriculture.

Ultra-fast forecasts

In the face of climate volatility, this tool offers forecasts up to 40,000 times faster than traditional models. This exceptional speed is crucial for emergency management and short-term planning in sensitive domains such as civil security and outdoor event management.

Increased forecast precision

This technology stands out for an accuracy improved by up to 50% compared to the most advanced forecasting systems. It covers varying time scales, from nowcasting (24 hours) to medium term (14 days), which is particularly beneficial for sectors heavily dependent on weather conditions such as agriculture and natural resources management.

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