The startup’s tech targets a persistent pain point in solar energy: the output losses caused by dirt, dust, sand, pollen, and snow buildup on panels. In some cases, soiling can cut efficiency by up to 60%, resulting in both performance loss and expensive cleaning schedules.
Swish Solar's approach combines two integrated technologies: a nanotech coating that passively removes debris, and an AI-powered monitoring platform that tracks panel cleanliness and predicts when action is needed. Together, they aim to automate solar panel maintenance at scale—without using a drop of water.
Real-world pilots are already underway, including a deployment with Renko Energy across a dozen solar facilities in Turkey. These early customers point to reductions in downtime and maintenance costs, while improving energy yield—especially in arid and dusty regions where traditional cleaning methods are both frequent and water-intensive.
As solar grows into one of the world’s most dominant energy sources, the focus is shifting from installation to operational efficiency. That means every lost percentage point—whether from equipment degradation or environmental buildup—affects both ROI and grid reliability.
While self-cleaning coatings are not new, Swish’s angle lies in its combined hardware/software strategy. Rather than relying on scheduled cleaning or reactive maintenance, asset operators get a data-backed view of when and where performance losses are happening. This shift from reactive to predictive cleaning helps reduce unnecessary maintenance, while maximizing uptime.
With customers already onboard in North America and the Middle East, the new funding will support product scale-up, team expansion, and continued refinement of the AI platform.
Backed by one of Canada’s leading tech incubators, the company is positioning itself as part of the next wave of cleantech infrastructure—where automation isn't just for tracking generation, but for sustaining it.
