Calvin wants to help save the planet by applying AI to home energy audits.

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When you're looking for a startup idea that can slow climate change, you can become an expert on home energy assessments. At least, that's what happened to the founders of Calvin, a French startup that's using computer vision and machine learning to make it easier to audit homes for energy efficiency.

Clémentine Lalande, Pierre Joly and Guillaume Sempé started looking at home energy efficiency audits because renovations would have a huge impact on energy consumption and reducing CO.2 Emissions But, like the rest of the construction industry, most companies in this space do not use technology to improve their processes.

“Europe has 300 million homes to renovate over the next 30 years,” Calvin CEO Lalande told TechCrunch. “But the construction industry is the second least digitized sector after agriculture.”

In France, the National Housing Agency (ANAH) has set an ambitious target of reaching 200,000 renovated homes in 2024 alone. But artisans simply can't keep up, and the climate suffers as a result. In general, the regulatory landscape is favorable for this type of startup in Europe.

Founded in October 2023, Kelvin is a pure software play. The company doesn't want to create a marketplace of service providers, and unlike Enter, another Germany-based home energy assessment startup covered by TechCrunch, doesn't want to be a customer-facing product either.

Instead, the startup has assembled a small team of engineers to build its own AI model that specializes in home energy assessments using machine learning. The company uses open data, such as satellite images, as well as its own training dataset with millions of images and energy assessments.

“We count more than 12 proprietary, semi-public or open data sources that provide information about the building and its thermal performance. So we're using fairly standard segmentation techniques, to detect specific features. are analyzing satellite images with machine learning models, such as the presence of adjacent buildings, solar panels, collective ventilation units, etc.,” said Lalande.

“We also do this on the data we collect ourselves. We have developed a remote inspection tool with a bot that tells the person there what images and videos to collect,” he added. said “Then we have models that count radiators in videos, detect doors, detect ceiling heights, and determine the type of boiler or ventilation unit.”

Kelvin doesn't want to use 3D technologies like LiDAR because he wants to build a tool that can be used at scale. It lets you use ordinary photos and videos, which means you don't need a modern smartphone with a LiDAR sensor to record room details.

A startup's potential clients could be construction companies, the real estate industry, or even financial institutions looking to finance home renovation projects – financiers, in particular, looking for accurate valuations before making a decision. I can be

In the company's first tests, its home energy ratings were accurate within 5% of old-fashioned ratings. And if it becomes the go-to tool for these audits, it will be much easier to compare one home to another and one renovation to another.

The startup has now raised €4.7 million ($5.1 million at today's exchange rate) with Racine² and a not-so-cheap investment from Bpifrance. Seedcamp, Rise Capital, Kema Ventures, Motor Ventures and several business angels also participated in the round.

Image credit: Calvin
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