Inspiration

We’ve all been in this situation: wanting solar but not knowing how many panels fit, what the output will be, or if the investment makes sense. I’ve had the same issue myself, and realized how much people need simple guidance instead of complex calculators.

What it does

SolarVision AI analyzes satellite rooftop data, local weather history, and smart algorithms to guide users step by step. Enter your address, draw zones on your roof map, and instantly see how many panels fit, if it’s too much for the area, predicted energy output, and a clear performance score (Excellent, Good, Fair).

How we built it

We combined satellite imagery APIs, live weather data feeds, and predictive algorithms to calculate solar potential. The web app features a map-based interface so anyone can visualize their roof and get guided recommendations.

Challenges we ran into

Designing an interface that feels guided and not overwhelming was a real challenge. We wanted users with little to no knowledge about solar panels to feel confident from the first click. That meant balancing technical details with simplicity: providing clear steps, visual cues, and instant feedback without flooding the user with data. The goal was to make the experience feel like having an expert by your side, guiding you through the process in a way that’s intuitive, supportive, and easy to follow.

Accomplishments that we're proud of

Especially, turning a complex, expert-only process into a guided, easy experience.

What we learned

  • Everyone struggles with the same uncertainty when starting with solar.
  • Making it visual, helps and makes it easy to use.
  • Local data (weather, shading, roof type) is crucial for useful insights.

What's next for Solar Vision AI

  • Adding cost–benefit analysis with payback period estimates.
  • Predictions using Solar models specs.
  • Offering API access for installers and energy companies.
  • Connecting users directly with trusted solar providers.

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