Weather Forecasting
1 / 5
Physics-informed AI models like EPT-2 beat traditional ECMWF HRES forecasts on key energy variables across all lead times, improving accuracy for wind, temperature, and solar radiation.
2 / 5
Jua runs complete about 2.5 hours ahead of competing operational forecasts, so traders act on fresher data and gain a timing edge.
3 / 5
EPT-2e ensemble forecasts outperform the 50-member ECMWF ENS mean on RMSE and CRPS, giving better-calibrated probabilities for tail-risk events.
4 / 5
The Jua platform exposes 25+ models through a single REST API and Python SDK with Apache Arrow support, cutting integration time from quarters to days for quant teams.
5 / 5
Book a demo with Jua to benchmark EPT-2 against your current forecast provider and see the full energy-trading stack in action.
Jua's physics-informed AI delivers 24x daily forecasts, beating ECMWF on wind & solar accuracy. Give your trading desk a real edge. Book a demo today.