Research
1 / 5
AI energy analytics tools now beat traditional NWP by delivering hyper-local forecasts, demand signals, and trading intelligence that update up to 24 times per day.
2 / 5
EPT-2 beats ECMWF HRES on every lead time from 0–240 hours for 10 m wind, 100 m wind, 2 m temperature, and surface solar radiation, while EPT-2e beats the 50-member ECMWF ENS mean on RMSE and CRPS.
3 / 5
Accuracy gains translate directly to P&L: a 1 GW wind portfolio can save ~€1.5 M per year and a 1 GW solar portfolio ~€3 M per year from a four-percentage-point improvement.
4 / 5
Jua for Energy combines physics-constrained models with the Athena agent to convert forecasts into natural-language briefings, benchmarks, and backtests in ~90 seconds, supporting intraday and day-ahead workflows.
5 / 5
Talk with the Jua team to benchmark EPT-2 against your current provider and see the 2026 accuracy and cadence advantage in your own portfolio.
Discover the top 12 AI analytics tools for energy in 2026. Jua delivers hyper-local forecasts that beat ECMWF — saving up to €3M/year. Explore now.