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The engine

From sensor to decision

Trained in millions of data points, integrating 22 million hexagons of variable size for the most sophisticated sea grid in the world and vertically integrated from sensor to decision, auditable end-to-end, and validated by the operators who actually sail the ships.

Multimodal fleet data

We ingest live AIS feeds, satellite data, vessel particulars, and real-world reports, giving us a proprietary multimodal dataset that no pure-software competitor can replicate.

Auditable source lineage

Every data point traces back to its source so our models are auditable and every customer knows exactly what's driving the recommendation.

Maritime ETL & quality

Our ETL pipeline enforces schema validation applies domain-specific cleaning rules built from actual vessel operations across the Oceans, not generic ML preprocessing borrowed from other domains.

Operator-grounded benchmarks

We validate against ground truth from live pilot programs with major operators, meaning our benchmarks aren't academic leaderboards but real-world voyage outcomes: fuel burned, ETA accuracy, weather avoidance decisions, and regulatory compliance.

Explainable Like Never Before

Natural-language justifications for masters, charterers, and auditors. Audit-ready outputs for CII, EU ETS, and FuelEU Maritime compliance reporting.

Integration

Built for systems,
not just screens

RESTful API with full OpenAPI 3.0 specification. Embed route intelligence into any system.

The fastest way to
optimize a voyage

VesselFront's intuitive API and documentation make it easy to get started, and easy to iterate. One endpoint, five agents, sub-second response.

Explore the docs 
const vf = require('vesselfront')('vf_live_...');

const route = await vf.routes.optimize({
  vessel_imo: '9315800',
  from:        'HAIFA',
  to:          'RIO DE JANEIRO',
  depart:      '2026-03-14',
  mode:        'fuel_efficiency',
  constraints: {
    cii_target: 'A',
    max_wave_m: 4.5,
  },
});

console.log(route.fuel_saving);  // "12.4%"
console.log(route.reasoning);    // LLM explanation
import vesselfront as vf

client = vf.Client('vf_live_...')

route = client.routes.optimize(
  vessel_imo='9315800',
  from_port='HAIFA',
  to_port='RIO DE JANEIRO',
  depart='2026-03-14',
  mode='fuel_efficiency',
  constraints={
    'cii_target': 'A',
    'max_wave_m': 4.5,
  })

print(route.fuel_saving)   # "12.4%"
print(route.reasoning)     # LLM explanation
curl -X POST https://api.vesselfront.com/v1/routes/optimize \
  -H "Authorization: Bearer vf_live_..." \
  -H "Content-Type: application/json" \
  -d '{
    "vessel_imo": "9315800",
    "from": "HAIFA",
    "to": "RIO DE JANEIRO",
    "depart": "2026-03-14",
    "mode": "fuel_efficiency",
    "constraints": {
      "cii_target": "A",
      "max_wave_m": 4.5
    }
  }'
VesselFront vf = new VesselFront("vf_live_...");

RouteResult route = vf.routes().optimize(
  RouteRequest.builder()
    .vesselImo("9315800")
    .from("HAIFA")
    .to("RIO DE JANEIRO")
    .depart("2026-03-14")
    .mode("fuel_efficiency")
    .constraint("cii_target", "A")
    .constraint("max_wave_m", 4.5)
    .build()
);

System.out.println(route.getFuelSaving()); // "12.4%"
System.out.println(route.getReasoning());  // LLM explanation
vf := vesselfront.NewClient("vf_live_...")

route, _ := vf.Routes.Optimize(context.Background(),
  &vesselfront.RouteParams{
    VesselIMO: "9315800",
    From:      "HAIFA",
    To:        "RIO DE JANEIRO",
    Depart:    "2026-03-14",
    Mode:      "fuel_efficiency",
    Constraints: map[string]any{
      "cii_target": "A",
      "max_wave_m": 4.5,
    },
  },
)

fmt.Println(route.FuelSaving) // "12.4%"
fmt.Println(route.Reasoning)  // LLM explanation

Take VesselFront to the Sea

Integrate at headquarters or use our system browser-free and for all types of connections. Download our app to your computer of choice and try our marine version for use even at a 64 kbps VSAT link.

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