Predictive maintenance for vessels that are at sea, not online.
AI maintenance for ships at sea, where cloud connectivity is unreliable and the regulator wants every decision auditable. The full inference loop runs on-vessel, on customer-owned hardware.
// that are at sea, not online · inside the perimeter
Cloud AI ends at the harbour.
A ship at sea has unreliable bandwidth, hostile network conditions, and regulators that want every operational decision traceable. Shore-based predictive maintenance systems assume connectivity that does not exist mid-voyage.
Fleet operators end up with two systems: a shore-side dashboard that is always out of date, and an on-vessel toolkit that has no AI assistance at all. Maintenance decisions get made on intuition, and the regulator gets a thinner audit trail than the ship deserves.
On-vessel inference, shore-side reporting.
Limit Signal: Maintenance for fleets runs the full inference loop on-vessel. Engine, hull, propulsion, navigation, and cargo systems are monitored locally; decisions and evidence sync to the shore when the link is available.
- 01
Multi-system condition monitoring per vessel
Models ingest engine performance, hull stress, propulsion telemetry, navigation signals, and cargo-system status. Each vessel learns its own normal operating envelope from its own voyage history.
- 02
Failure prediction with sea-state context
Predictions account for sea state, route, weather, and cargo load, not just instantaneous readings. A bearing temperature reading means different things in calm seas and in heavy weather.
- 03
Regulator-ready evidence per decision
Every maintenance decision lands in the on-vessel evidence store with the inputs, the model version, the confidence, and the responsible officer. The regulator gets a full record without depending on shore-side reconstruction.
- 04
Shore-side fleet view, opportunistic sync
Decisions and evidence sync to the shore office over whatever connectivity is available, including intermittent satellite links. The shore-side fleet manager sees per-vessel state without depending on the link being live.
Runs at sea. On the vessel.
Limit Signal: Maintenance for fleets is designed for vessels that may go weeks without reliable shore connectivity. The full application, model weights, sensor history, and evidence trail run on the on-vessel hardware. No off-vessel dependency at runtime.
When the vessel is in port or within range of a reliable link, aggregated metrics and evidence records sync to the shore office. Sync is governed by the customer DPA; no telemetry leaves the vessel by default.
- Where it runs
- On-vessel hardware (purpose-built or rugged general-purpose), sized per vessel and per asset count. Survives loss of all external connectivity.
- What stays on the vessel
- Engine and equipment telemetry, voyage history, model weights, predictions, evidence records, and officer decisions.
- Who controls the data
- The fleet operator is the controller, on each vessel and shore-side. Limit Systems is a processor under the per-deployment DPA.
- Evidence for the regulator
- Per-decision records compatible with the customer's class-society and flag-state audit requirements. Available on the vessel for inspection without shore-side access.
Every application runs on the same sovereign platform. The identity layer, the audit trail, the policy engine, the evidence retention. Built once, used by all. Explore the platform →
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See it in your environment.
Walk us through your perimeter, your evidence requirements, and the systems already in place. We'll show you how the deployment looks.