50% better forecasts,
powered by local data
Our engineers have developed cutting-edge ML models that are able to deliver key meteorological forecasts with building level precision.
By combining client sensor data + our proprietary ML, you get forecasts up to 50% more precise than existing global models.
Hyper-local, not regional
Existing forecast models operate globally on kilometer resolutions which fall short in use-cases where decimal level precision matters.
We took a different approach, and decided to build custom hyper-local models for each client's asset location. Built from the ground up for that location, tailored to the local influences and geography.
meteo variables
minutes
better accuracy
One Weather API for
Easy Integration
Data Types
From temperature to wind speed, pressure to solar irradiance, our AI models can forecast up to 25 different meteorological variables.
Data Resolution
Temporal
- Hourly updates, possibility for sub-hourly update intervals on some variables
- Up to 48 hours ahead on each run of the ML model
Spatial
- Down to an asset/building level
Data Sources
We combine your on-site sensor data (if existing) with nearby weather stations, and a range of forecasts from high end global models including ECMWF, Météo-France, UK Met Office & DWD.
Load Limits
EarthCare.ai has robust, auto-scaling API that can handle as many forecasting locations as needed, as well as fast access to forecasts.
Documentation
Get in touch with our team and we’ll gladly walk you though implementation details and examples.
Use Cases
Use Cases
Energy Forecasting
Infrastructure Monitoring
Energy Demand
Book a Demo Call
Our team has over 10 years of experience with weather and climate data. Our work has been featured in Forbes, BBC, The Guardian, NY Times, Washington Post, WIRED...
Book a meeting with us to discuss your exact use-case, and how EarthCare.ai can bring you value.