AshFI brings AIS-derived vessel intelligence, physics-informed health indicators, and remaining useful life estimation to any fleet, without requiring sensor integration or onboard hardware. It is the data layer that feeds ASHMOP, the operational digital twin, and stands on its own for operators who need fleet visibility today.
Why AshFI
Most fleet intelligence tools stop at position, route, and ETA. AshFI goes further: using only a vessel's IMO number, publicly available AIS data, and engine specifications, it estimates engine load, fuel efficiency trends, and remaining useful life, using the same physics-informed modelling approach that powers ASHMOP's predictive maintenance engine. No sensors. No integration. No waiting for a digital twin rollout.
What AshFI does
Vessel Health Snapshot
Enter an IMO number and receive an instant, physics-informed estimate of engine load, fuel efficiency, and degradation trend, derived from AIS movement data and engine design specifications.
Remaining Useful Life Estimation
Weibull-based RUL modelling, the same methodology used in ASHMOP's predictive maintenance core, applied at fleet scale without requiring onboard sensors.
Fleet Risk Benchmarking
Compare vessels across a fleet on consistent health and risk indicators, helping technical superintendents prioritise attention where it matters most.
Feeds the Digital Twin
AshFI data and ASHMOP's operational digital twin are designed to work together. Insights generated here can flow directly into a full ASHMOP deployment as a fleet's digital twin maturity grows.
How it works
Request a demo with your vessel's IMO number or fleet details
Receive a sample analysis showing the kind of insight AshFI generates
Our team follows up to scope a fleet-wide deployment suited to your operation
AshFI and the Asheriv suite
AshFI is one of three products in the Asheriv maritime intelligence suite. AshSIM connects shipyard design and build data to the digital twin. ASHMOP is the full operational digital twin platform. AshFI provides fleet intelligence without requiring sensor integration, serving as both a standalone tool and a feed into ASHMOP.