Why things need to change

Our Solution

Paralas integrates a phase-synchronized gimbal with a dual RGB/thermal camera setup. The payload flies beneath a certified partner drone and remains aligned with the rotating blade at all times.

Our cloud-based models detect cracks, delamination, and thermal hotspots—sending real-time, actionable alerts to operators and maintenance planners.

How it works

Paralas provides full rotor blade inspection during rotation, without turbine shutdown, without climbers, and without emission-intensive vessel trips. Our solution combines drone automation, thermography, and AI into a scalable offshore inspection service.

1. Launch from CTV or platform

After airspace coordination, the drone takes off from a CTV or offshore platform near the turbine.

2. Active rotor tracking

The gimbal synchronizes with blade tip speed (RPM), making the spinning blade appear stationary to the camera.

3. Full rotor inspection

All three blades are inspected outside the turbine’s wake zone. Once complete, the drone automatically returns to base and uploads the data.

4. AI-based damage classification

Captured RGB and thermal footage is analyzed by our AI model. It detects and classifies defects, hotspots, and other anomalies.

5. Real-time insights via dashboard

Operators can view the inspection live through our online dashboard. Results are available immediately after the flight and ready for O&M planning.

Frequently asked questions

Is this legal under EASA/ILT regulations?

Yes. We operate with certified partners under the Specific Category framework, including SORA risk assessments and pre-flight airspace clearance.

Which drones do you use?

We use certified offshore drones from trusted partners. The payload is modular and compatible with various drone platforms.

What happens to the data collected during inspections?

Inspection data remains the client’s property. However, it is shared with Paralas by default to improve our AI models, critical for increasing damage detection accuracy.

Data is processed securely, never resold, and only used for model training. Clients may opt out of reuse.

Can the system be used for onshore turbines?

Yes, provided the local airspace and environment allow it. Our solution is especially effective in hard-to-reach areas such as mountainous terrain or remote locations where rope access or lifts are impractical.

What types of damage can the system detect?

Our AI is trained on visual and thermal blade imagery, focusing on three primary damage categories:

• Leading edge erosion

• Trailing edge cracks

• Delamination

These account for the majority of visual degradation affecting energy yield and structural integrity.

How are results delivered?

Inspection results are accessible via the Paralas web dashboard. All images, damage types, and classifications are clearly organized by turbine and blade. Clients can export data or integrate results with existing maintenance systems via APIs.

Future updates will include trend analysis and predictive maintenance based on historical damage progression.

About Paralas Offshore

Paralas Offshore was founded by two students with backgrounds in Electrical Engineering (TU Delft) and Artificial Intelligence (University of Groningen). What began as a high school project evolved into a startup focused on wind industry inspection solutions.

After pivoting to offshore inspections, we won a startup competition—giving us the resources to build Paralas professionally.

We combine technical agility with a hands-on mindset, in an industry where innovation is often slow and fragmented. Our university ties give us access to top engineering talent and advanced lab facilities.

Paralas is young, flexible, and data-driven, exactly what this industry needs to make inspections smarter, safer, and more scalable.