Ireland's remarkable renewable energy story was our spark. With over 60% of the country's power now coming from renewables, offshore wind isn't just an environmental talking point, it's a live national priority. Yet the tools available for assessing offshore wind sites were either too expensive, too complex, or not accessible to the people who needed them most: early-stage developers, researchers, and policymakers trying to make fast, informed decisions. WindSite was born during a 30+ hour hackathon where we pushed ourselves to build something genuinely useful for this space. As the hours wore on, our approach evolved significantly. What started as a straightforward data visualization idea grew into something more ambitious. We leaned into Recursive Language Models to power the assessment engine, allowing the system to iteratively refine its analysis of a site's potential rather than producing a single static output. That recursive approach turned out to be the key insight: offshore wind assessment isn't a one-shot problem, it's an iterative one, and our architecture reflects that. The hackathon pressure forced us to strip the idea down to what mattered most: speed, accessibility, and accuracy, and build around those three pillars from the ground up.

WindSite—Offshore Wind Energy Assessment

AI feasibility assessment for offshore wind energy projects.

AI feasibility assessment for offshore wind energy projects.