Use Cases

In a constantly changing supply chain faced with supply uncertainties, a leading logistics service provider is implementing advanced machine learning models to improve forecast accuracy and enable efficient personnel and warehouse planning.

Learn how a multinational manufacturer of insulation materials not only drastically improved its forecast accuracy by implementing an AI-supported forecasting tool, but also significantly increased operational reliability and cost efficiency.

A major German automotive manufacturer is experiencing volatile demand in the after sales business and is no longer satisfied with the current forecasting approach. With pacemaker.ai, a transparent solution was found.

In the automotive supplier industry, newly introduced products and the fluctuating ordering behavior of OEMs require an efficient planning method. Discover how an improved planning strategy not only saves time but also increases the accuracy of inventory forecasts and avoids common problems such as excess inventory and supply bottlenecks for our customer.

Learn how pacemaker.ai uses machine learning to overcome the challenges of predicting oil and air filter sales, improving forecast accuracy by 41% and drastically reducing planning effort.

Discover how pacemaker.ai improved forecast accuracy and efficiency in the warehouse operations of a leading tire supplier through advanced AI forecasts. This technology makes it possible to precisely predict daily and weekly output quantities and at the same time drastically reduces manual planning effort.

Learn how pacemaker.ai is revolutionizing supply chain planning for aerospace suppliers with cutting-edge, automated predictive models to ensure accurate and efficient inventory management.