Our Solutions

We build and operate digital twins of wind turbines.
Automated vibration analysis based on AI and physical modelling for next generation data-driven condition-based maintenance.
What if your turbines could intelligently trigger their own maintenance when needed?
We develop the next generation of condition based prescriptive & predictive maintenance systems.
Our end-to-end solutions for automated drive train vibration analysis, are based on cutting edge artificial intelligence and sophisticated physical modelling.
This allows us to predict mechanical failures or emerging malfunctions of the wind turbines. And the best: over time, the turbines themselves learn when their components are at risk and can autonomously trigger a maintenance request.


Our Expertise

Big Data & Internet of Things

Implementation, pipelining and effective computing with end-to-end solutions for big data architectures.

Digital Twins of your Assets

Combining physical and data-driven models  to enable a thorough health condition analysis.

Automated Failure Prediction

Real-time, cloud-based and automated failure prediction using vibration, operation and meteorological data.

Predictive Condition Monitoring

Comprehensive and intuitive condition-based predictive health analysis.



Automated vibration analysis of drive train components based on sophisticated physical modelling and AI algorithms.

The annea Zebra dashboard informs you about your wind turbines’ health status in real-time and gives you a highly advanced failure and root cause prediction based on digital twins of the components.
read more…


Drone image recognition for automated early failure detection in structural components.
read more…


With many years of experience in the wind industry, ANNEA aims at enhancing condition monitoring and predictive maintenance of wind turbines to minimize the risk of unexpected downtime and unplanned repair.

Every wind farm, and even every wind turbine operates in a distinct way. Inflow, operational conditions, wake, component age and environmental impact vary throughout the farm and affect the failure behaviour of each turbine differently. With this, each turbine has a unique fingerprint and no generic failure prediction algorithms can be applied. We therefore developed a tailored automated predictive maintenance tool to make your wind turbines more reliable and profitable. Let us find the perfect solution for your needs!

About us

We are a team of mechanical, industrial and aerospace engineers, computer scientists, Internet of Things (IoT) and artificial intelligence experts. With many years of experience in the wind industry and a strong background in engineering, we provide solutions for predictive and prescriptive maintenance of wind turbines based on profound domain knowledge, advanced machine learning techniques and sophisticated reliability modelling techniques.

Supported by

Our Vision

ANNEA helps you to look into the future and to prevent your assets from failing unexpectedly. Our aim is to digitalize renewable energy assets and to revolutionize and automate operation and maintenance (O&M), condition monitoring and failure prediction, without setting apart a deep mechanical understanding of the machines.