Harness the power of artificial intelligence to predict energy demand, renewable generation, and market conditions with unprecedented accuracy. Our advanced forecasting models are specifically designed for energy portfolios, helping utilities and BRPs optimize their operations and reduce costs.

Maximize operational efficiency and reduce costs
Enhance decision-making with accurate, real-time predictions
Scale dynamically to adapt to changing conditions and portfolio needs
Portfolio Forecasting for Utilities & BRPs: Predict your entire energy position — including consumption, generation, and net imbalance — to reduce market penalties and improve planning.
Direct Multi-Step Forecasting (DMSF): When real-time historical data is available, we train dozens (or hundreds) of models per site or portfolio using direct multi-step techniques. This results in high-resolution forecasts (15-min to hourly) with superior accuracy.
Custom Models per Asset or Region: Models are adapted to your portfolio composition — whether that's industrial loads, residential demand, wind parks, or solar farms.
AI/ML & Deep Learning Stack: We use XGBoost, LightGBM, neural networks (LSTMs, TCNs), and hybrid architectures, depending on the nature of your data and forecasting horizon.
Rolling & Real-Time Forecasting: Models are continuously updated with live weather and operational data, enabling forecasts to adapt to real-world fluctuations.
Forecast Delivery & Integration: Access sub-hourly, hourly, and daily forecasts via API, automated email reports, or web dashboards integrated into your systems.
Balance Responsible Parties, utilities, aggregators, and large renewable portfolio owners seeking precise, adaptive, and automated forecasting.
Lower imbalance costs, better market positioning, and smarter dispatch with high-precision forecasts that outperform conventional benchmarks.
Transform your energy operations with our ai-powered forecasting for energy portfolios. Contact us today to schedule a consultation and see how we can help your business.