Inconsistent sensor inputs
Missing or delayed data
No visibility into data quality
Most fleets don’t realise they have a data health problem due to:
As a result:
Teams spend hours validating numbers
Performance issues are misdiagnosed
Wrong decisions are made
The challenge
When bad data looks like bad performance
A vessel appears to be underperforming. You schedule a hull cleaning. But the issue is not the vessel. It’s the data.
In many cases, data fragmentation limits operational value and fleet optimisation potential.
Collects high-frequency data from Neuro or any onboard system (enriched with weather and AIS data)
Ingest
Applies validation, filtering, and standardisation across all vessels
Process
Builds vessel-specific behavioural and performance models using AI
Model
Provides a structured, unified dataset via APIs, cloud warehouse, or DeepSea applications
Deliver
How it works
From raw data to trusted intelligence
The result? One consistent dataset across the entire fleet.
Flexible data access via APIs or cloud warehouse
Continuous data quality monitoring (data health layer)
Vessel-specific AI models (performance, fouling, engine behaviour)
Integration with BI tools and internal systems
Key capabilities
Built to manage data at scale
Neuro is the onboard hardware gateway connecting directly to vessel systems to collect high-resolution operational data with minimal installation complexity.
Without a unified digital backbone, operators face, True operational efficiency begins with structured and reliable vessel data.
Missing or delayed data
Noisy or out-of-range signals
Stuck or repeated signals
Data inconsistencies across sources
The system flags issues, in real time, to maintain data integrity and continuously checks for:
The intelligence layer behind Vessel Intelligence