How Deutsche Bahn redefines forecasting using Chronos models – Now available on Amazon Bedrock Marketplace

This post is co-written with Kilian Zimmerer and Daniel Ringler from Deutsche Bahn.

Every day, Deutsche Bahn (DB) moves over 6.6 million passengers across Germany, requiring precise time series forecasting for a wide range of purposes. However, building accurate forecasting models traditionally required significant expertise and weeks of development time.

Today, we’re excited to explore how the time series foundation model Chronos-Bolt, recently launched on Amazon Bedrock Marketplace and available through Amazon SageMaker JumpStart, is revolutionizing time series forecasting by enabling accurate predictions with minimal effort. Whereas traditional forecasting methods typically rely on statistical modeling, Chronos treats time series data as a language to be modeled and uses a pre-trained FM to generate forecasts — similar to how large language models (LLMs) generate texts. Chronos helps you achieve accurate predictions faster, significantly reducing development time compared to traditional methods.

In this post, we share how Deutsche Bahn is redefining ...