Three levers, one optimal route.
Every crossing is a trade-off between speed, cost and safety. SeaRoute-Py makes it explicit and quantified.
From two ports to the ideal route, in four steps.
Define the crossing
Port of departure, port of arrival, vessel type and service speed. The corridor is set in a few seconds.
Connect the data
Wind (GFS), currents (CMEMS) and swell (WW3) are loaded in real time along the corridor — overlaid in one click.
Run the optimisation
The algorithm computes several candidate routes according to your priority: Fast, Eco or Safe.
Compare and export
Duration, fuel, distance and risk side by side. You select the route, you export it to the bridge.
The sources your teams already know.
No black box. SeaRoute-Py relies on the standard oceanographic models and validates them against measured data. You know where every field comes from.
Metocean models
Wind, currents and swell from the reference operational models — aggregated and interpolated along your corridor.
In-situ validation
The fields are compared against real measurements (buoys, ADCP, tide gauges) for credible conditions, not theoretical ones.
AI + physics hybrid
A deterministic core accelerated by AI emulation: routes computed in seconds, not hours.
Measured gains, not promised ones.
SeaRoute-Py relies on OceanData Consulting’s observation-model fusion engine. The same rigour that reduces forecast bias serves to make every route you export reliable.
Ready to optimise your crossings?
Give us a line and a vessel — we show you the optimised routes and the expected gains in a dedicated demonstration.