Case Study: Intergrid cuts forecast deployment time by 80% with Nixtla's TimeGPT

Intergrid - Customer Case Study

Intergrid, an energy technology company, faced significant challenges in scaling its forecasting operations as it expanded into new European power markets. Their existing traditional time series models required extensive manual setup for each new geography, creating a multi-day engineering bottleneck that hampered growth. To support its expansion safely and reliably, Intergrid needed a fast, accurate, and scalable forecasting solution and turned to vendor Nixtla for its TimeGPT service.

By implementing Nixtla's TimeGPT, Intergrid replaced its manual forecasting process with a unified foundation-model-powered workflow. The solution integrated in under an hour and provided configurable, context-aware predictions. This resulted in an 80% reduction in deployment time, a 20% improvement in forecast accuracy, and the ability to onboard new industrial heat customers within just one week, allowing the analytics team to focus on strategic optimization and market expansion.

Intergrid

Jaakko Hyppönen

Head of Analytics