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Maritime & Shipping

AI for fleet operations that cuts fuel costs, port delays, and compliance exposure

You get voyage optimisation agents, predictive maintenance, port logistics intelligence, and IMO compliance automation. All running on your cloud, connected to your existing fleet systems, with governance built in.

or

Built on your AWS, Azure or GCP tenant. IMO-ready. Flag-state compliant.

Container ship at sea with port infrastructure
30 days

Proof of concept

12-18 weeks

To measurable ROI

Your cloud

AWS, Azure or GCP

Fuel, port time, and compliance are the three margin killers in shipping. AI addresses all three.

Your fleet generates terabytes of AIS data, engine telemetry, weather feeds, and port schedules every week. Most of it sits unused. The carriers that convert this data into routing decisions, maintenance schedules, and compliance documentation are the ones reducing cost per TEU while their competitors absorb it.

We build AI agents that connect your vessel data to your operational decisions from voyage optimisation and predictive maintenance to port call scheduling and IMO 2023 CII compliance, with audit trails your flag state and P&I club can verify.

Up to 12%

fuel savings reported by AI-optimised voyage routing (McKinsey, 2024)

$3.7M

average annual saving per vessel from predictive maintenance (BCG X, 2023)

20-30%

reduction in port idle time with AI berth scheduling (Deloitte Insights, 2024)

47%

of shipping firms report CII compliance as top operational risk (McKinsey, 2024)

Connected

From vessel sensor to compliance record, in one workflow

We connect your AIS feeds, engine telemetry, port management systems, weather APIs, and ERP to AI agents that optimise voyages, predict equipment failures, schedule port calls, and generate the CII and EEXI documentation your flag state and classification society require

Vessel & Port Data

AIS, IoT sensors, ERP, port systems and weather

AI Agent
ModelYour choice
HostingYour cloud
Workflow Engine
  • Approval gates
  • Human-in-loop
  • Audit logging
Your Cloud Tenant

AWS, Azure or GCP

Operational Output
  • Voyage reports
  • Compliance records
  • Fleet analytics
5 Integrations
4 Connections

What we deliver for maritime and shipping enterprises

Maritime AI

From voyage planning to port operations, governed, auditable, enterprise-ready

Voyage route optimisation

Generate fuel-optimal routes for every voyage automatically.

ROI

Fuel savings8-12%
CO2 reduction10%
ETA accuracy+25%

Process

1

Aggregate voyage data

Weather forecasts, current patterns, port congestion, charter constraints, and vessel performance data ingested in real time

2

Model optimal routes

AI calculates fuel-optimal routes accounting for weather windows, ECA zones, speed profiles, and arrival time requirements

3

Deliver voyage plans

Recommended routes with fuel estimates, ETA projections, and risk assessments pushed to bridge systems and operations desks

Sources

Originally published: McKinsey QuantumBlack, 'AI in Shipping Operations' (2024); BCG X, 'Digital Shipping' (2023), reproduced for illustrative purposes

Predictive maintenance

Predict component failures before unplanned drydock events.

ROI

Unplanned downtime-40%
Maintenance cost-25%
Off-hire days-35%

Process

1

Collect equipment data

Engine telemetry, vibration sensors, lubrication analysis, and maintenance history streamed from vessel systems

2

Predict failures

ML models identify degradation patterns and forecast remaining useful life for critical components

3

Schedule maintenance

Service recommendations aligned to next port call, spare part availability, and drydock windows

Sources

Originally published: McKinsey QuantumBlack, 'Predictive Maintenance in Maritime' (2024); Deloitte Insights, 'Smart Shipping' (2023), reproduced for illustrative purposes

Port call optimisation

Coordinate arrivals and berths to cut port idle time.

ROI

Port idle time-25%
Demurrage costs-30%
Berth utilisation+20%

Process

1

Integrate port data

Berth availability, tide windows, cargo readiness, and terminal capacity data aggregated from port systems

2

Optimise scheduling

AI models coordinate arrival times, berth assignments, and cargo sequences to minimise waiting time

3

Coordinate stakeholders

Automated notifications to terminal operators, agents, and vessel crews with optimised schedules

Sources

Originally published: BCG X, 'Port Operations Analytics' (2024); McKinsey QuantumBlack, 'Smart Ports' (2023), reproduced for illustrative purposes

CII and EEXI compliance automation

Calculate CII and EEXI scores with voyage-level recommendations.

ROI

Reporting time-60%
Compliance accuracy99%+
Rating improvementProactive

Process

1

Track emissions data

Fuel consumption, distance travelled, cargo carried, and operational parameters captured per voyage

2

Calculate compliance scores

AI computes CII ratings and EEXI scores in real time with projected annual trajectories

3

Generate compliance reports

Flag-state-ready documentation with corrective action recommendations when ratings deteriorate

Sources

Originally published: McKinsey QuantumBlack, 'Decarbonisation in Shipping' (2024); Deloitte Insights, 'IMO 2023 Compliance' (2023), reproduced for illustrative purposes

Fuel consumption analytics

Pinpoint factors driving excess fuel burn across your fleet.

ROI

Fuel cost reduction8-15%
Hull cleaning ROIOptimised
Fleet visibilityReal-time

Process

1

Baseline fuel performance

Historical consumption data normalised against weather, load, speed, and hull condition variables

2

Identify excess consumption

AI isolates the root causes of fuel overuse: hull fouling, suboptimal trim, engine degradation, or routing

3

Deliver actionable insights

Vessel-specific recommendations for hull cleaning timing, speed profiles, and operational adjustments

Sources

Originally published: BCG X, 'Fleet Decarbonisation Analytics' (2024); McKinsey QuantumBlack, 'Fuel Optimisation' (2023), reproduced for illustrative purposes

Cargo and container tracking

Track containers from booking to delivery with exception alerts.

ROI

Exception detection85% faster
Customer enquiries-40%
Dwell time-20%

Process

1

Connect tracking data

Container IoT sensors, terminal operating systems, and carrier APIs integrated into unified visibility platform

2

Detect exceptions

AI flags delays, temperature deviations, route anomalies, and customs holds in real time

3

Automate notifications

Proactive customer and operations alerts with root cause analysis and revised ETAs

Sources

Originally published: AWS Case Study, Maersk; McKinsey QuantumBlack, 'Container Logistics AI' (2024), reproduced for illustrative purposes

Trade document processing

Extract and reconcile shipping documents in minutes, not days.

ROI

Processing time-75%
Error rate-60%
Document throughput3x

Process

1

Ingest documents

Bills of lading, customs forms, letters of credit, and certificates of origin captured from email, EDI, and portals

2

Extract and validate

AI extracts key fields, cross-references against booking data, and flags discrepancies for review

3

Reconcile and route

Validated documents matched to shipments and routed to customs brokers, banks, and compliance teams

Sources

Originally published: Deloitte Insights, 'Trade Finance Automation' (2024); BCG X, 'Digital Trade Documents' (2023), reproduced for illustrative purposes

Esa Henttinen

SVP, Fleet Operations Technology, Wärtsilä

Esa Henttinen

"Azure AI gives us the ability to process engine telemetry from thousands of vessels simultaneously. We can predict component failures weeks before they happen, schedule maintenance at the next port of call, and avoid the unplanned drydock events that cost our customers millions per incident"

Originally published: Microsoft Customer Stories — Wärtsilä — reproduced for illustrative purposes

01 / 04

How we work in maritime and shipping environments

Maritime AI is only valuable when it connects to the data your fleet already generates. We start by mapping your existing sources: AIS feeds, engine telemetry, port management systems, weather APIs, and ERP. Then we identify the one use case where AI will create the most immediate, measurable cost reduction.

Everything we build runs on your cloud tenant. Your vessel data, your operational records, your compliance documentation. None of it goes to a third-party platform. Your flag state, classification society, and P&I club can audit the system directly.

01

Data and use case mapping

We assess your existing fleet data sources, identify the highest-value AI use case, and map it to your compliance and operational requirements.

02

30-day proof of concept

A working AI agent on your cloud, connected to your vessel or port data, with demonstrable output in 30 days.

03

Governance by design

Audit trails, compliance records, and explainable outputs built in, structured to meet flag state and classification society requirements.

04

Scale in 12-18 weeks

From one validated workflow to measurable operational ROI across your fleet or port operation.

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