Tracks cargoes and forecasts freight rates
- Who we serve
- Private Sector
- Category
- Energy, utilities & resources
- Value
- Revenue
- Human role
- Human sets the rules
- Maturity
The problem
Without freight & vessel-tracking analytics, teams in trading & supply make these calls on averages and instinct, because AIS, port data are not joined up, and the value in the data goes uncaptured.
How it works
Freight & vessel-tracking analytics tracks cargoes and forecasts freight rates. The approach relies on ML, satellite data. It draws on AIS, port data and is typically owned by teams in trading & supply. The main constraint is data quality. Where the human comes in: chartering teams. It is scaled at leading organisations and piloted elsewhere; examples include Trading houses; Kpler and Vortexa-type platforms.
Where the human comes in
Chartering teams
What it needs
AIS, port data
What to plan for
Data quality
In the field
Trading houses; Kpler and Vortexa-type platforms
Public deployments by other organizations, listed for context. Not Sphere projects.