Stockholm-based climate-tech startup Improvin' has raised €3.5 million in a seed funding round led by Paulig's venture arm PINC. In addition, Pale Blue Dot and Dynamo Ventures, a US-based supply chain VC, and Axel Johnson's FoodBridge also participated.
The startup provides an AI-driven sustainability performance platform to measure and reduce their primary production emissions and increase biodiversity. With this tool, companies, processors, and farmers can maximize efficiency and report the sustainability of their value chains. To date, the startup has signed contracts with over 10,000 farmers owning 500,000 hectares in Sweden and other parts of Europe.
"Improvin's platform makes a complex task much easier both through automatic satellite data and user-friendly interfaces. It is also the perfect starting point to work on reducing the environmental impact. We have tested the platform with some of our wheat suppliers and this is the best platform they have come across, which can also be seen in the current traction of the company. This is why we invested. That and an amazing team with roots from farmer families", stated Marika King, Head of PINC.
The investment will further allow the company to develop its agri-food industry-focused sustainability performance platform as it prepares to roll out its services to the German, Belgian, French, and Dutch markets.
One thing that many food and beverage companies that have set climate targets have in common is the difficulty of measuring, verifying, and thereby reducing indirect emissions produced by their value chain. As a result, it takes a significant reduction in greenhouse gas emissions to reach the set climate targets. These emissions account for approximately 90% of the greenhouse gas emissions.
As of January 2023, the EU's Corporate Sustainability Reporting Directive established a standard for sustainability reporting by companies. The proposed measures will require companies to report value chain emissions (scope 3).
With Improvin's technology, growers can get verified Scope 3 calculations traced down to land management units without manually gathering the data. Customers benefit from the scalability of remote sensing and the precision of growers' inputs. Using machine learning algorithms and deep neural networks, high-frequency and high-resolution satellite imagery is combined with artificial intelligence to verify the data.