Bearing AI screenshot

What is Bearing AI?

Bearing AI is an AI platform designed to optimise maritime shipping operations whilst maintaining compliance with environmental regulations. The tool automates decision-making across emissions monitoring, route optimisation, and fleet deployment by analysing operational data in real-time. It helps shipping companies reduce fuel costs and carbon footprint by simulating different operational scenarios and comparing vessel efficiency across schedules. The platform tracks compliance with regulations like the Carbon Intensity Indicator (CII) requirement and provides actionable recommendations to improve performance. It requires no new hardware or complex system integrations, working with existing operational data. Bearing AI is suitable for operations teams managing multiple vessels, fleet planners comparing deployment options, and sustainability officers tracking environmental impact across their shipping operations.

Key Features

Emissions Monitoring

Track environmental impact in real-time for regulatory compliance

Scenario Forecasting

Simulate operational outcomes to support informed decision-making

CII Optimizer

Monitor and forecast Carbon Intensity Indicator scores

Fleet Deployment Optimizer

Compare vessel efficiency across different schedules and routes

Performance Analytics

Analyse fuel consumption trends and weather impact on vessels

Proactive Recommendations

Receive actionable insights to improve operational efficiency

Pros & Cons

Advantages

  • Reduces fuel costs and carbon emissions through optimised operations
  • Automates compliance tracking for environmental regulations
  • Integrates with existing systems without requiring new hardware
  • Provides data-driven insights for fleet allocation decisions
  • Handles large-scale operations across multiple vessels

Limitations

  • Requires detailed operational data from vessels for optimal results
  • Learning curve for users new to maritime analytics platforms
  • Pricing may be significant for smaller shipping companies
  • Effectiveness depends on the quality of vessel data inputs

Use Cases

Optimising fuel consumption across a fleet of container ships

Ensuring CII compliance for individual vessels

Comparing efficiency of different vessels for route assignment

Tracking and reducing overall fleet carbon emissions

Simulating impact of operational changes before implementation