Apex Flow: Formula 1 lap-time predictions that stay accurate

Apex Flow predicts Formula 1 lap times in real time from live telemetry, weather, tire, and historical race data, a problem where the model is the easy part and keeping it accurate race after race is the real work. So we built the platform as a production MLOps system, not a notebook.

The pipeline covers the complete lifecycle: automated data ingestion and feature engineering, model training, containerized FastAPI serving, and, critically, monitoring with drift detection that triggers automated retraining when the data distribution shifts, as it does every time regulations, tires, or weather change. Docker keeps every stage reproducible from laptop to deployment.

Lap-time predictions run in real time from live telemetry, weather, tyre and historical data.

Drift detection triggers retraining automatically, so accuracy holds race after race, and Docker keeps every stage reproducible from laptop to deployment.