For forty years, time series forecasting has meant a whole project: hire data scientists, engineer features, train, tune, retrain. Half the use cases your teams could imagine never made the cut - the business case was too thin.

Time series foundation models break that equation. They deliver accurate forecasts out of the box - no training, no tuning, no feature engineering. In months of rigorous tests against live industrial forecasters and peer-reviewed literature benchmarks, we found they match or beat the competition at a fraction of the cost and time.

In this session, we share the honest results - where these models shine and where they still fall short - the use cases that suddenly clear the business case, and a practical checklist to rethink your forecasting roadmap before your sector catches on.