I've built up data on speed, draft, weather and how much fuel was u…

What We'll Build

• A voyage fuel prediction model trained on your historical speed, draft, weather, and consumption data, delivered as an API your planners can query in real time.
• A bunkering planner interface where operators input upcoming voyage parameters and receive fuel estimates with confidence intervals.
• A continuous retraining pipeline so the model improves as new voyage data accumulates.

How It Works

• Historical logs are cleaned and feature-engineered (speed-through-water, displacement proxy from draft, Beaufort/wave height from weather records) then used to train a gradient-boosted or neural regression model.
• At voyage planning time, inputs are sent via MQTT or REST to a shore-side inference service; edge preprocessing on board can handle real-time adjustments mid-voyage.
• Model performance is monitored against actuals after each voyage, triggering retraining when drift is detected.

Next Step

Upload a sample of your voyage logs (CSV or export from your VMS/noon reports) along with any data dictionary in the Mind4Ship client portal — we'll assess data quality, identify gaps, and scope a working prototype within days.