OffShore
OnShore

We Detect Blade Damage Early, Before It Costs You $250K+

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AI-powered blade health monitoring trained on real damage events — not static thresholds

Monitoring 24/7 across offshore and onshore wind turbine blades, Windrover detects, categorizes, and tracks hidden blade damage before failure happens.

1000+ACTIVE
WIND TURBINES
80+WIND TURBINE
MODELS
450+CAT3+ DAMAGE
DETECTED
%94DETECTION
ACCURACY RATE

Continuous Monitoring

Windrover system is active across 10 countries, providing real-time health data for hundreds of turbine assets.

4.2M+
HOURS OF DATA COLLECTED
Warning
BLADES SAVED
40+

By early detection of critical blade failures.

ROI Delivered
ROI Delivered
%500

1 prevented failure can cover Windrover's lifetime cost.

Plug and Play
TRUE PLUG AND PLAY
<5 minInstallation

No wiring, no integration, start: no downtime, no disruption to operations.

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Testimonials

Trusting By Leading
Energy Companies

Before Windrover, our team had to manually inspect turbine blades by going to each turbine and listening for unusual sounds that could indicate a developing issue. The process was time-consuming, subjective, and entirely manual. Since implementing Windrover, this workflow has become fully automated. Instead of relying on manual checks, we can access detailed reports through an intuitive dashboard and instantly identify which wind farm, turbine, or blade requires attention. This has significantly improved our operational efficiency, reduced inspection effort, and given us much greater confidence in our blade monitoring process.

Avatar
Ahmet AYTAÇİşletme Müdürü, Galatawind

Before implementing Windrover, our blade inspections were limited to annual drone or rope-access inspections. Since adopting the system, we have gained continuous visibility into the condition of our blades. Windrover detects even the slightest changes in blade acoustic signatures, automatically generates detailed reports, and enables continuous blade health monitoring. This allows us to identify potential issues much earlier and make more informed maintenance decisions, rather than waiting for the next scheduled inspection.

Avatar
Kemal PALAİşletme Müdürü, Genpa Yenilenebilir Enerji

Windrover sistemi, kanat sağlığının sürekli izlenmesi konusunda bakım süreçlerimize önemli katkı sağladı. Sistemin akustik analizleri sayesinde kanatlarda oluşabilecek hasar belirtilerini erken aşamada tespit edebiliyor, gerekli saha kontrollerini ve bakım faaliyetlerini zamanında planlayabiliyoruz. Sürekli izleme yaklaşımı, kanatların durumuna ilişkin daha fazla görünürlük sağlayarak bakım kararlarımızı yalnızca periyodik kontrollerle değil, saha verileriyle de desteklememize olanak tanıyor. Bu sayede potansiyel sorunları büyümeden değerlendirme, bakım planlamamızı daha etkin yönetme ve planlı bakım yaklaşımımızı güçlendirme imkânı elde ettik. Windrover’ın kolay uygulanabilir yapısı ile sağladığı güvenilir analizler, operasyonel güvenilirliğimizi artıran ve bakım süreçlerimizin verimliliğine katkı sağlayan önemli avantajlar sundu.

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Eda ÖRENElektrik Mühendisi, Briza Wind

There are a lot of lightning strikes in our farm, by notifying those lightning damages us in advance, we can take action more quickly and minimize our losses as much as possible. When we are able to predict and monitor wind turbine blade damages in a shorter period of time, we will achieve maximum profit with minimum losses as much as possible. Thanks to Windrover, damages can be detected at an earlier stage. I believe that companies working in the wind energy sector should buy these technological products.

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Gürkan ERKANField Officer, Briza Wind

Having 24/7 monitoring is something we would definitely recommend to everyone. It’s easy for us to explain to our team the benefits of a system that can be monitored continuously. I can show our team the data we received any time. This way, we can clearly identify any damage based on based on the data provided by Werover. We can tell our team to conduct inspections earlier. This way, we save time and reduce production losses and costs. By doing so, we can minimize expenses and downtime.

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Sedat TOPALOperations Manager, Türkay Alternatif Enerji

One of the things we appreciated most about Windrover was how quick and straightforward the installation process was. We also received positive feedback from our policyholders regarding Windrover's responsive, solution-oriented approach and the overall quality of its service. The system's ability to detect issues at an early stage enabled our policyholders to assess and address potential problems before they escalated. As a result, Anadolu Sigorta has been able to further strengthen its preventive insurance approach.

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Anadolu Sigorta

Before Windrover, our team had to manually inspect turbine blades by going to each turbine and listening for unusual sounds that could indicate a developing issue. The process was time-consuming, subjective, and entirely manual. Since implementing Windrover, this workflow has become fully automated. Instead of relying on manual checks, we can access detailed reports through an intuitive dashboard and instantly identify which wind farm, turbine, or blade requires attention. This has significantly improved our operational efficiency, reduced inspection effort, and given us much greater confidence in our blade monitoring process.

Avatar
Ahmet AYTAÇİşletme Müdürü, Galatawind

Before implementing Windrover, our blade inspections were limited to annual drone or rope-access inspections. Since adopting the system, we have gained continuous visibility into the condition of our blades. Windrover detects even the slightest changes in blade acoustic signatures, automatically generates detailed reports, and enables continuous blade health monitoring. This allows us to identify potential issues much earlier and make more informed maintenance decisions, rather than waiting for the next scheduled inspection.

Avatar
Kemal PALAİşletme Müdürü, Genpa Yenilenebilir Enerji
Problem

The Cost of Late Detection is Massive

Without Windrover
WITHOUT WINDROVER
Failure
CAT4-CAT5
Failure

Reactive Approach: Failure-Driven Maintenance

Damage goes undetected until catastrophic failure occurs.

  • Hidden damage escalates over time
  • Cat 5 failure (severe structural damage)
  • Blade replacement cost ~$1M
  • Downtime: minimum 3 months
  • Unplanned maintenance & lost production

From $1M failures and months of downtime -> to early detection and controlled maintenance.

What we do

Scalable capabilities for every challenge

1

Detected by Windrover

Identify blade anomalies early with continuous monitoring

Check
02.11.2025

Damages are recorded on Windrover Dashboard.

Dashboard 1
2

Alert

Analyze damage type, severity, and location

Check
21.11.2025

Damage escalation from Cat 2 to Cat 3 is reported on Windrover Dashboard

Dashboard 2
3

Decide and Act

Act at the right time

Check
03.12.2025

On the first windless day, drone inspection is planned and damaged analyzed.

Dashboard 3
Shield info

Detected in November.Verified in December. Months before the scheduled July inspection, and before catastrophic failure.

The Difference

Not Just Detection.Damage Intelligence

Traditional inspections react to visible damage. Windrover detects hidden damage before failure happens.

TRADITIONAL METHOD
Annual Inspections

Annual Inspections

Energy Tech Damage often remains undetected for months.

Visible Damage Only

Visible Damage Only

Hidden and internal damage goes unnoticed.

Manual & Time-Consuming

Manual & Time-Consuming

Slow reporting delays critical decisions.

Reactive Maintenance

Reactive Maintenance

Issues discovered late lead to unplanned downtime.

Higher Risk, Higher Cost

Higher Risk, Higher Cost

Catastrophic failure risk and costly repairs.

Info

Designed for turbines that don't stop— in environments that don't forgive.

Capabilities

Powerful Insights. Actionable Intelligence.

Turn turbine data into real-time decisions with AI-powered monitoring, analysis, and reporting.

Personalized Interface
Overview
Damage Insights
Damage Progression
Working Flow

How It Works

Technical Overview

01

Listen

Windrover continuously captures acoustic signals from turbine blades during operation.

02

Detect

Machine learning identifies unusual vibration/acoustic patterns linked to early blade damage.

03

Process

Signals are securely processed and transmitted to the Windrover platform in real time.

04

Classify

The system classifies damage type and severity (Cat 1–Cat 5) and tracks progression over time.

05

Alert

Teams receive clear alerts with risk level, location, and recommended next steps.

06

Act

Operators plan repairs early, prevent escalation, reduce downtime, and avoid costly blade replacement.

From hidden damageto controlled maintenance before failure.
Awards Background
Werover on the Nasdaq Tower — November 12 2025
Awards & Recognition

Awarded For Innovation In Blade Intelligence

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The Emirates Energy Award, Dubai

Research and Development

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Microsoft Women Leaders of Technology, 2022

Successful Female Entrepreneur of the Year

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Halkbank Women Entrepreneurs Competition

Zero Waste and Sustainability Category Winner

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Febeliec Energy Award 2025, Belgium

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