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From raw sensor data to operational decisions

We combine three disciplines that rarely exist under one roof. That combination is our edge.

01

AI & Time-Series Intelligence

The core of what we do is intelligence — transforming streams of raw sensor data into clear, actionable insight about the condition and future behaviour of an asset.

Machine learning for anomaly detection and early degradation identification
Time-series analysis across multiple sensor channels simultaneously
Uncertainty quantification — our models tell you how confident to be
Predictive algorithms for fault progression and optimal intervention timing
AI agents that express asset health in plain language for operators
Physics-informed machine learning that understands the underlying mechanics
Bayesian inference for real-time probabilistic state estimation

Live Condition Monitoring

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Blade condition metrics from an onshore wind turbine, monitored continuously by Tarucca.

02

Optical & Multi-Vendor Sensing

Offshore infrastructure demands sensors that can survive extreme environments, avoid electromagnetic interference, and deliver the signal quality needed for AI analysis.

Photonic vibration sensors with very high sensitivity and full EM immunity
Multi-axis measurement: vibration, strain, deflection, and temperature
Multi-vendor sensor integration — hardware agnostic
Edge computing architectures for offshore data collection with limited connectivity
Secure and ruggedised data pipelines for critical infrastructure
Field deployment experience in harsh offshore environments
Photonic sensing systems
03

Structural Dynamics & Digital Twins

We bring the physics. Understanding how a structure actually behaves — under wave loads, fatigue cycling, and environmental stress — is what separates meaningful insight from noisy data.

Structural dynamics modelling for complex offshore assets
Fatigue and load analysis for critical components (blades, mooring lines, cables)
Digital twin development that updates from real sensor measurements
Physics-based simulation for mooring systems and turbine structures
Condition-based maintenance frameworks grounded in actual asset behaviour
Integration with DNV certification frameworks

Digital Twin Simulation

Platform Mooring 1 Mooring 2 Mooring 3

Physics-informed digital twin of a floating offshore wind mooring system.

Our AI stack for offshore infrastructure

Every piece works together — from the sensor on the asset to the decision on the operator's screen.

1

Sensors

Multi-vendor sensor arrays measuring vibration, strain, motion, temperature, and environmental conditions.

2

Edge Processing

On-site data collection with local pre-processing — filtering, compression, quality checks — even with intermittent connectivity.

3

Secure Data Pipeline

Validated pipelines that ingest, clean, and enrich time-series data. Handles multi-channel, multi-rate sensor feeds.

4

AI Models

Anomaly detection, predictive maintenance, probabilistic degradation models, and uncertainty-aware RUL estimation.

5

Digital Twin

Physics-informed digital representations that update from real data — comparing measured vs. predicted asset behaviour.

6

Operational Decision Support

Dashboards, alerts, and AI-generated condition summaries that give operators clear, actionable guidance with confidence levels.

Where we apply it

Active Project

Wind Turbine Blade Monitoring

Condition and structural health monitoring using photonic sensors and AI anomaly detection. Currently deployed onshore — moving offshore in Q2 2026.

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TKI Offshore Energy — Funded R&D

MOOR-LIFE: Mooring Line Intelligence

Probabilistic digital twin and AI-based remaining useful life estimation for floating offshore wind mooring systems. Developed with TU Eindhoven. TRL 3→5.

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Active Project — with Seekable

Subsea Cable Localisation — ZeeCAIbel

AI correction algorithms that dramatically improve the accuracy of subsea power cable surveys — enabling faster inspections and better maintenance decisions.

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Want to understand our approach in depth?

We are happy to walk you through our technology stack and how it applies to your specific asset or challenge.

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