SAPPI optimizes Energy Management with AI-Driven Bidding strategies

Leverage machine learning models to refine bidding strategies, reducing energy expenses while improving efficiency.
Analyze market conditions in real-time to sell excess energy at higher prices, transforming energy optimization into a new revenue stream.
Enable faster, data-driven insights and scale automated energy management across multiple sites.

A smart approach to energy cost reduction

SAPPI, a leader in paper, pulp, and sustainable packaging, continuously seeks ways to optimize operations while reducing costs and improving sustainability. As part of its broader AI and MLOps transformation, SAPPI implemented an advanced energy analytics solution to improve energy related decision making and optimize energy market participation at its Maastricht mill.

Navigating a complex energy market

Managing energy consumption efficiently while participating in the energy market presented several challenges:

Adopt AI & Cloud for Smarter Energy Management

Identify the Best Bidding Prices in a Volatile Market

Automate & Standardize Data Processing

Reduce Manual Effort & Increase AI Adoption

SAPPI and Orange Business - Energy Analytics

AI-Powered Energy Analytics & Automated Bidding

SAPPI partnered with Orange Business to develop an AI-driven energy optimization framework using Google Cloud technologies. This solution enables real-time analysis and bidding in the energy market, ensuring SAPPI can maximize cost savings and revenue opportunities.

Machine learning models analyze and predict energy market fluctuations to determine optimal bidding prices.
Automated data ingestion pipelines collect and process energy market data from fifteen different APIs every day.
Continuous model optimization and retraining ensures AI-driven bidding strategies remain accurate and aligned with market trends.
Near-real-time reporting & insights via Looker provide energy traders with a clear and automated overview of market conditions and AI model performance.
Significant improvements have been made compared to the previous solution in place, resulting in significant savings for SAPPI.

Scalability for Future AI Innovations

With the ML at Scale framework designed by Orange Business, SAPPI has built more than just a solution for manufacturing efficiency—it has established a scalable AI-driven infrastructure that will continuously evolve.

By automating AI workflows, enhancing predictive analytics, and ensuring seamless data integration, SAPPI is now well-positioned to drive continuous innovation and operational excellence in the European market.

With the MLOps framework in place, SAPPI has already successfully developed and deployed three AI-driven use cases in production, running over 20 machine learning models. These models operate seamlessly within the framework, benefiting from automated deployment, monitoring, and retraining. By standardizing AI workflows, SAPPI can now efficiently scale future AI projects, ensuring faster time-to-value and streamlined operations across different business areas.

Key Figures

offices in Europe

4,200

employees

Don't take our word for it. Hear what our customers say.

PieterJan Geens, Head of Data & Analytics, SAPPI

"By integrating AI-driven energy analytics, we’ve transformed our approach to making energy related decisions. We now have automated insights and forecasting models that enable us to make optimal decisions to reduce energy costs."

SAPPI Europe