What happened
Decathlon, a global sporting goods retailer, generates weekly demand forecasts for tens of thousands of products spanning multiple continents.
The company deployed Chronos-2 on AWS, improving forecast accuracy by 11 to 15 points while reducing operational complexity.
Weekly inference runs on CPU-only instances at a cost of about $0.03.
Why it matters
This example shows that a large retailer can achieve significant forecasting gains without investing in expensive GPU infrastructure, thanks to low-cost, CPU-only inference.
The combination of accuracy improvements and reduced complexity makes advanced AI forecasting practical for high-volume, multi-region operations, potentially encouraging similar adoption across the retail industry.
Key facts
Decathlon forecasts weekly demand for tens of thousands of products across multiple continents.
Chronos-2 on AWS improved forecast accuracy by 11–15 points.
Weekly inference costs about $0.03 on CPU-only instances and cuts operational complexity.
What to watch next
Watch whether other large retailers follow Decathlon's lead in adopting Chronos-2 or similar cost-efficient forecasting models.
See if this sparks broader use of CPU-only inference for AI workloads that were previously considered GPU-dependent.