Artificial Intelligence (AI) has increasingly taken the spotlight for software companies looking to quickly leverage large amounts of data to create actionable results. Solar design and proposal platform provider Aurora Solar is embracing AI in its product offerings as the industry matures.
Aurora’s AI uses machine learning algorithms to construct 3D models of homes and their roofs in about 30 seconds. Launched in 2022, the AI platform has been continually honed based on customer feedback. With AI, solar companies can use predictive tools to identify top prospects, enable sales teams with design tools, and improve design efficiencies with automation.
“Move fast. Speed is one of your main advantages over large competitors,” said Sam Altman chief executive officer of OpenAI.
Aurora’s AI is applied to its full project cycle from lead capture to initial proposal generation, to final system design.
The software is trained on nearly half a million site models and generates imagery based on satellite and lidar data. Aurora said the end result is a fast and accurate proposal generation.
Aurora said its automated design tool has performed well when compared to manual designs. Aurora AI performed as well or better than a human 63% of the time for simple roofs, 83% of the time for moderate roofs, and 76% of the time for complex roofs, said the company.
As for speed, Aurora reports that its design generator vastly outpaced human designs. While a standard design service may range from 30 minutes to 24 hours, Aurora says its tool produced a design in 32 seconds on average, based on 340 trial runs of the software.
Over the past year, solar sales teams and designers used Aurora AI 1.6 million times, with strong sequential monthly growth, said the company.
“Aurora’s AI-powered software and onboarding services helped us transform traditional roofing specialists into solar roofing specialists in a day, and even helped one dealer get their first sale in week one,” said Mark Stevens, solar application manager, CertainTeed.
Aurora said it has the following goals to improve its AI-backed services:
- Applying improved land parcel data to improve automatic identification of property boundaries
- Updating the U.S. lidar database with the most recent and high resolution data available
- Increasing model training efficiencies and accuracy by consuming more training data faster
- Streamlining product features by consolidating AI SmartRoof and AI Roof faces
- Expanding Aurora AI’s capabilities to more markets outside of the U.S.
- Exploring and investing in more solar sales- and design-specific AI use cases
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