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Cut marine fuel burn
with physics,
not guesswork.

NAVIMIND computes the lowest-fuel voyage that still hits your ETA window, and prices the EU ETS exposure of every option before you sail. A physics-grounded routing and fuel-efficiency engine for RoPax and deep-sea fleets.

6 vessel archetypes 5 optimization objectives EU ETS priced per voyage
NAVIMIND route intelligence dashboard showing an optimized Piraeus to Heraklion voyage with the live AIS track, the live weather grid, and the fuel saving
01 · The problem

Fuel is the largest controllable cost at sea.
Now carbon has a price too.

Conservative voyage plans leave fuel on the table

Crews default to design speed on the shortest path. Because power scales with the cube of speed, a small, deliberate speed reduction inside the ETA window can cut burn dramatically, but only if it is computed, not guessed.

EU ETS turned CO₂ into a line item

Shipping now surrenders emission allowances for voyages touching EU ports, phased in through 2024 and 2025. Every tonne of fuel not burned is an allowance not bought, so carbon cost is now coupled directly to routing decisions.

02 · What NAVIMIND does

One engine, from sea state to spreadsheet.

It plans the voyage, models the physics behind the burn, and translates the result into fuel tonnes, CO₂, and EU ETS cost, so the trade-off is visible before the lines are let go.

Lowest-fuel routing within an ETA window

NAVIMIND evaluates the full speed-and-heading envelope to find the cheapest path in fuel that still arrives inside a hard ETA window: slow-steam where it pays, hold speed where it must.

objective: MIN_FUEL

EU ETS exposure, priced per voyage

CO₂ is derived from fuel using IMO-standard carbon factors, then converted to ETS allowances under the current phase-in and intra/extra-EU coverage rules: a euro figure per option, not an afterthought.

CO₂ → allowances

Five objectives, one model

Switch the optimization target without changing the physics: minimize fuel, time, cost, or emissions, or run BALANCED to weigh them together. The same per-leg model scores every candidate edge.

MIN_FUEL · MIN_TIME · MIN_COST · MIN_EMISSIONS · BALANCED

Six vessel archetypes, fully parameterized

RoPax ferry, container feeder, Supramax bulker, Aframax tanker, post-Panamax box ship, and LNG carrier, each built from real naval-architecture parameters rather than generic black-box lookups.

RoPax-first, deep-sea ready
03 · How it earns its keep

Physics in, euros out.

NAVIMIND models the real physics of the hull, the sea, and the wind using recognized naval-architecture standards, not a black-box estimate. So every plan it proposes is grounded in how your vessel actually behaves, and every number traces back to a published method your team can audit.

The saving is computed, not assumed. The same model scores your baseline plan and your optimized plan, so the delta is real, repeatable, and defensible.
1

Reads the real sea state

live weather, hull, wave & wind

Every leg is scored against the conditions it will actually meet: the hull through the water, the waves on the bow, and the wind on the topsides, from live weather along the route.

2

Finds the cheapest plan that still arrives on time

full speed & heading envelope

NAVIMIND weighs the whole range of speeds and headings open to the voyage and returns the lowest-fuel plan that still lands inside a hard ETA window: no missed schedules to save fuel.

3

Respects the vessel's limits

within installed power

Plans stay inside what the engine room can actually deliver. NAVIMIND never proposes a speed the vessel cannot hold, so the recommendation is one the crew can sail as-is.

4

Turns fuel into euros and CO₂

fuel → emissions → EU ETS

Each option comes with its fuel tonnes, its CO₂, and its EU ETS allowance cost, so the financial and carbon trade-off is on the table before the lines are let go.

5

Auditable end to end

traceable to published standards

No black box. Every figure traces back to a recognized, published method, the kind of provenance a class society, an investor, and a chief engineer can each stand behind.

04 · What it adds up to

Numbers you can trace back to a method.

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Vessel archetypes
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Optimization objectives
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Physical resistance models
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Combined fuel saving
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Representative fuel saving

Combining optimal speed selection with weather routing, we estimate a 7–12% fuel reduction against an operator's actual filed plan, while still arriving inside a ±30-minute ETA window.

Grounded in peer-reviewed evidence: roughly 4 to 6% from speed optimization and 3 to 5% from weather routing individually (container-ship studies; the IMO cites up to ~10% for some vessels), which overlap rather than simply add when combined. On our Piraeus–Heraklion demo voyage the engine reports a larger figure measured against a full-design-speed baseline — a deliberately conservative "unoptimized" assumption, not an operator's real plan.

05 · Why it holds

A physics core, sharpened by a data moat.

  • Not a black box

    Every output traces to a physical parameter and a published method. That is auditable for a class society, an investor, and a chief engineer alike.

  • Live AIS calibration

    Continuous AIS ingestion lets the model calibrate per ship from observed behaviour, turning a generic archetype into a vessel-specific efficiency curve over time.

  • RoPax-first, deep-sea ready

    We start where schedules are tight and fuel is dominant (short-sea RoPax), then extend the same engine across the deep-sea archetypes it already models.

06 · Where it goes

A working engine, with a clear path ahead.

The engine is live today. From here, the roadmap is about widening coverage and deepening per-vessel calibration, turning a strong model into an ever-sharper one as the data grows.

Shipped

Interactive routing demo live

Multi-voyage selector, fuel-trend charts, weather overlays, and per-voyage ETS cost against a mock API.

In progress

Higher-resolution routing building

Finer routing grids, so the geometric divergence between the baseline and the optimized track becomes visible on the map.

Next

Live AIS + weather automation planned

Automated collection feeding per-ship physics calibration: the data moat that turns archetypes into vessel-specific models.

Where it grows

Per-vessel calibration at scale planned

Tuning each ship to its own observed behaviour, so a generic archetype becomes a vessel-specific efficiency curve.

Where it grows

Deeper fleet coverage planned

Extending the same engine across more vessel classes and trade lanes, from short-sea RoPax out to the deep-sea fleet.

Where it grows

Continuous accuracy gains planned

As the data moat grows, the model keeps sharpening, every voyage observed makes the next prediction tighter.

Let's talk

See the engine run on your route.

Bring a voyage and a vessel class. We will show the baseline, the optimized plan, the fuel delta, and the EU ETS cost side by side, with every number traceable to the model behind it.