Case Study: Dexter Energy achieves scalable, real-time AI forecasting with Google Cloud Platform

Using AI to optimize the forecast and trade of renewable energy

Dexter Energy, a Netherlands-based renewable energy startup, needed a scalable way to power its AI models for short-term power forecasting and energy trade optimization. Using Google Cloud Platform, along with support from Xebia, it set out to handle real-time data from customers, weather, markets, and producers while keeping performance, reliability, and costs under control.

Google Cloud Platform helped Dexter Energy build a cloud-native architecture using services like BigQuery and Google Kubernetes Engine, plus serverless and event-driven tools for efficient processing. The result was simpler administration, lower infrastructure and operating costs, and highly scalable real-time analytics; its AI models now help energy suppliers reduce balancing costs by up to 35%.

Dexter Energy

Danny Bennett

DevOps and MLOps Engineer