Most fleets generate significant volumes of high-frequency vessel data. Few can rely on it consistently across the fleet, over time. The problem is not data collection. It is how vessel data is operated after collection.
Analytics teams flag incorrect outputs. Performance reports show numbers that don't add up. Optimisation tools return nonsensical results. The data failure happened weeks before anyone noticed. There are no active monitoring or alerts. The data layer is silent until something downstream breaks.
Fuel consumption reported on one vessel does not match the same metric from another. Same sensors, different values. Teams cannot compare performance across the fleet. When the underlying data cannot be trusted, vessel-to-vessel analysis becomes impossible.
The data is flowing. It exists. But accessing it means raising an IT project or involving a third party. Sharing a subset with a charterer requires a custom integration every time. A data scientist wanting to explore engine performance spends months extracting and reconciling before any analysis begins.
Adding a performance analytics tool requires aligning on data access with an existing vendor or creating new IT infrastructure. Each initiative is an independent project. Cost and lead time stay high. The organisation never builds the accumulated data capability that would let initiatives build on each other.
If these patterns are familiar, you are experiencing the reliability and usability gap at fleet scale. Trust breaks once, and adoption stalls. Teams that cannot rely on their data do not build on it. They work around it.
Treating vessel data as infrastructure means a different relationship between data and applications. Not just data collection for fuel optimisation. But instead a data foundation that enables fuel optimisation, performance management, compliance, predictive maintenance, and future use cases that do not yet exist.
Move data from ship to shore. No standardisation, no observability. What appears inexpensive at procurement becomes expensive in hidden labour and rework.
You inherit all responsibility with none of the tools to manage it.
Where your vessel data becomes dependable infrastructure.
The vessel data foundation. Operational reliability for fleet-scale data. You control what you do with it. Any analytics provider, any reporting system, any third party. The foundation serves multiple consumers and is independent of any single application.
Analytics-led, data collection bundled into a broader stack. Data access restricted, governed by the vendor's terms. Switching analytics means rebuilding data infrastructure.
Your data serves the vendor's applications, not yours.
The foundation sits between your vessel systems and your applications. These are the outcomes it produces for the teams that depend on vessel data.
New analytics vendor? New compliance requirement? New commercial reporting need? Each initiative builds on data that is already captured, standardised, and governed. Integration effort decreases with every addition. The foundation is the accumulated capability your organisation builds on.
Every signal standardised into a single fleet-wide model. Your performance team compares fuel consumption, shaft power, or any metric across the fleet without reconciliation. ISO 19848, DNV VIS, JSMEA, and custom naming served simultaneously from the same foundation.
Fleet-wide visibility into connection status, latency, data quality, and alerting when streams degrade or stop. Your operations team sees what needs attention in one place, not discovered three weeks later through a failed analytics output.
Structured APIs serve measurements, metadata, and statistics in whichever standard each system requires. Your data lake gets a clean feed. Your reporting tools get the format the regulator expects. Your data scientists get raw time series. One foundation, many consumers.
A charterer needs a data subset. An analytics vendor needs an API feed. A class society needs specific signals. Token-based access control means each new data consumer is a configuration decision, not a three-month integration project. You control exactly what each party sees.
Pull data into your own data lake, analytics platforms, or reporting tools through the API. The foundation delivers to wherever your organisation operates. No proprietary application layer between your data and your systems. Change downstream tools without touching the foundation.
Some of the world’s most demanding fleet operators run their vessel data on Raa Labs — and describe the difference in their own words.
“I have not seen any company that has come further in digitalizing ships’ operational data and delivering it to the actual decision-makers”
“Every charterer has unique requirements. With RaaEDGE we can tailor data deliveries to each partner, while at the same time meeting our own needs as a vessel owner”
At Nor-Shipping, we invite our customers to present — fleet operators sharing how they use vessel data infrastructure in their own operations.
Our customers on stage: Maersk, Eastern Pacific Shipping, Wallenius Wilhelmsen, and the Wilhelmsen Group presenting how they use the vessel data foundation.
Wallenius Wilhelmsen on building vessel data infrastructure at scale, and the operational discipline required to maintain it.
Captures data directly from vessel systems, standardises at the source, delivers to the cloud. Handles signal capture, local processing, buffering during connectivity loss, and secure transmission.
Brings data from existing onboard collectors into the foundation at the cloud level. No new hardware. No rip and replace. Data from existing collectors is ingested, contextualised, and standardised.
Both deliver into the same cloud environment. A fleet can mix both. The choice is made per vessel.
The Foundation is always Raa Labs. The Function can sit with you, or sit with us. Different vessels can operate under different models.
Access to the full data foundation, visibility and monitoring of data health handled by you.
For organisations with the internal capability to run vessel data operations with their own tools and processes.
Full visibility into data health across your fleet, you decide how to act.
For organisations where vessel data serves multiple teams, applications, or third parties, and where no one has a complete picture of data health across the fleet.
We operate the vessel data function on your behalf.
For organisations that have experienced what happens when vessel data reliability falls to whoever has time.
The operating model is a choice, not a permanent commitment. Different vessels can operate under different models. Platform service health is always Raa Labs' responsibility.
See how each model works in practiceThe foundation sits between your ship systems and your applications. It does not compete with them. It provides the reliable data layer that every downstream system depends on.
Operational responsibility for data health sits with the customer or with Raa Labs. Never blurred. Never shared informally. The operating model makes this explicit from day one.
Ingestion services, processing pipelines, storage, APIs, portal, monitoring infrastructure. Regardless of operating model, the platform is Raa Labs' responsibility.
Captured, contextualised, and served through APIs in any standard. ISO 19848, DNV VIS, JSMEA, or custom naming. Standardisation makes the data usable across teams. Open access makes it yours to deploy wherever you operate.
Every customer gets the same underlying foundation. Signal scope is unlimited under Self-Governed and Governed. What varies is the capability layer Raa Labs provides on top, and where operational responsibility for data health sits.
Different vessels can operate under different models. Models can shift as your internal capability matures or your fleet shape changes. The Function moves; the Foundation does not.
Three endpoint categories: measurements (time series), metadata (signal and vessel context), and statistics (aggregated data). Contextualised and uncontextualised signals available.
View documentationMost fleets collect vessel data. Very few can rely on it consistently across the fleet, over time. Signals differ between vessels, streams fail without anyone noticing, and every new analytics tool or reporting requirement becomes its own integration project. The problem is not collection. It is making vessel data work as dependable, fleet-wide infrastructure that multiple teams and systems can build on.
No. Cloud Connect brings data from existing onboard collectors into the foundation at the cloud level. No new hardware, no rip and replace. If you want to upgrade to onboard capture, RaaEDGE is the path. A fleet can run both.
It depends on your operating model. Under Self-Governed, your team detects and handles it. Under Governed, the monitoring infrastructure alerts you with diagnostic context. Under Assured, Raa Labs investigates and coordinates resolution without waiting for you to notice.
You can run multiple analytics providers on the same foundation. Analytics vendors build applications that consume data. Raa Labs builds the infrastructure that produces reliable data. The foundation sits underneath your analytics, not alongside it. You keep full control over which tools and providers you use.