How Aerones Is Redefining Wind Turbine Maintenance with Robots and AI

Could you briefly introduce yourself and your company?

My name is Jānis Kļaviņš, Sr. Account Executive for Aerones. Aerones is a robotics and AI company founded in 2018 in Riga, Latvia, with a second hub in Dallas, Texas. We are the world's leading provider of robot-enabled wind turbine inspection, maintenance, and repair services. Our customers - including NextEra, GE Vernova, Vestas, Enel, and Siemens Gamesa - represent more than 50% of the world's installed wind capacity, and we operate across more than 35 countries.

Our mission is straightforward: keep the world's wind turbines producing clean energy at peak performance, for longer, with less risk to the people who maintain them.

If you had to explain your project to someone who knows nothing about your industry, what would you say?

Wind turbines are among the tallest moving mechanisms on the planet, and keeping them healthy still depends on technicians dangling from ropes dozens of meters in the air - a model that is too slow, too dangerous, and far too understaffed to support the energy transition. In plain language: we send robots up the turbines so humans don't have to, and we do it with speed and quality that manual work can't achieve.

What sets you apart today in your market?

Three things.

• First, we don't sell robots - we operate them as a service, which means our customers get outcomes (a cleaned blade, a repaired leading edge, a certified lightning protection system) rather than equipment they have to learn to use.
• Second, our patented robotic platform covers the full lifecycle of the blade and tower - external and internal inspection, cleaning, coating, leading-edge erosion repair, and lightning protection system inspection - all under one provider, whereas the market is otherwise highly fragmented.
• Third, the scale of our data: servicing more than 10,000 turbines a year on four continents gives our AI models a dataset that most competitors simply can't match. The result is service that's roughly 4x faster with 10x less idle time than traditional rope-access work, and analytics for preventive maintenance planning for our customers.

What is your story with ENGIE?

Aerones has been actively working with ENGIE in Europe and the United States since 2024, doing hundreds of robotic internal blade and LPS inspections and several leading edge repair projects. Our main collaborators at ENGIE have been Nicolas Quiévy, Pragna Martin, and Jeremy Hellot. Areones chose to work and innovate with ENGIE because ENGIE’s global scale in energy infrastructure, strong focus on decarbonization, and commitment to digital transformation create an ideal environment for deploying advanced autonomous inspection and maintenance technologies. The partnership enables Areones to validate and scale its robotics solutions across real-world industrial assets while helping ENGIE improve safety, operational efficiency, predictive maintenance, and sustainability outcomes.

What will you be showcasing on the ENGIE booth at VivaTech?

Aerones will be showcasing our Gen 3 internal inspection crawler for wind turbine blade inspections. 

What is the one key takeaway you want visitors to remember after meeting you?

One key takeaway we want visitors to remember is that Aerones is transforming wind turbine maintenance with robotics that make inspections safer, faster, and more data-driven. Our Gen 3 internal inspection crawler demonstrates how innovation can reduce downtime, improve asset reliability, and help accelerate the future of clean energy together with ENGIE. 

This year’s VivaTech theme is “AI: Impact, not illusion”. What role does AI already play in your solution, and how do you see it evolving in the future?

AI is not a marketing layer for us - it sits at the core of every robot we deploy, and every operation we execute. Today it powers automated defect detection on blade imagery (identifying cracks, erosion, and delamination at sub-millimeter resolution), precision control of our repair and coating robots, and predictive analytics that tell wind farm operators which turbines need attention before failures occur.

Where we're heading: greater autonomy for the robots themselves, so a single operator can supervise multiple turbines simultaneously, and predictive models that move the industry from reactive repair to true condition-based maintenance. Our operations hub relies heavily on AI models that optimize route planning, weather conditions, expenses and the materials used in various projects. Every AI feature we ship has to translate into a measurable outcome: megawatt-hours recovered, downtime reduced, or a technician kept safely on the ground.

What is your next major challenge in the short or medium term?

Two challenges, running in parallel.

Short term: scaling our U.S. operations out of the new Dallas hub to meet North American demand, and bringing our offshore service capability to commercial scale, which is technically and logistically much harder than onshore.

Medium term: optimize our core processes using AI-enhanced software solutions and industrializing our robotic Leading Edge Repair system so it can be deployed at the volume the global fleet actually requires. The wind industry is staring down a serious technician shortage by 2030, and our challenge is to scale robotic capacity fast enough to close that gap.

If your innovation is fully successful, what will have changed in the world in five or ten years?

Three concrete shifts.

• One, no human will need to climb a wind turbine to maintain it - the dangerous part of the job moves into a control van on the ground.
• Two, the operating cost of wind energy drops significantly because turbines spend more time generating and less time idle, which makes wind cheaper than any fossil alternative without subsidy in most markets.
• Three, the lifespan of the global wind fleet extends by years, meaning every turbine already standing produces more clean electricity over its life.

Meet Aerones on ENGIE's Booth at Viva Technology on June 17-20 and learn more about them watching this video: