There’s a big wave of cutting-edge solutions in climate action. With several businesses having recently closed their financial rounds in this area, we were curious to know how they are using AI (artificial intelligence) and ML (machine learning) to save our planet – and the answers we found show promise.
Europe is extremely active when it comes to early-stage investments in purpose-driven companies. According to Atomico’s State of European Tech 2021, European investments are the largest in total global capital supporting early-stage purpose-driven tech businesses. This group includes planet-positive companies taking urgent action to combat climate change and its impact. Europe’s shares account for 61% of all funding at the Pre-Seed and Seed stages (<$5M) and 53% of the total funding invested across the Pre-Seed to Series B (up to $20M) stages.
From reducing emissions and identifying risk factors to trade transport and beyond, European startups aren’t so much working on a more powerful AI but rather trying to be smarter regarding where and how they use it.
DeepSea is a startup founded in 2017 by Konstantinos Kyriakopoulos and Roberto Coustas. The company is headquartered in London with a base in Athens, Greece, and raised €5 million in its last financial round led by Nabtesco Technology Ventures with participation from The Signal Group and ETF Partners in mid-2021.
DeepSea operates in the shipping industry, which is a massive part of the supply chain for global trade. Statista’s data shows that around 80 percent of goods are transported by ships – a significant cause of global pollution.
DeepSea Technologies adopts AI to make ships and voyages more efficient. In this case, AI – unlike other technological solutions – captures the unique characteristics of every individual vessel. With this data, DeepSea’s solutions provide crews with the “right answers” to questions like “What route should we travel? How fast? With what settings?” Implementing the recommendation allows ships to save around 10% more fuel during their voyages. As Angus Whiston, Communications Director at DeepSea Technologies, stated in our conversation, “This is not only commercially important – it’s also critical for meeting the new environmental regulations that are rapidly transforming the industry.”
DeepSea Technologies is now a team of 80 people and its solutions optimize hundreds of vessels on a daily basis.
Founded in 2020, Vaayu provides automated carbon tracking software built to empower retailers to cut their carbon emissions in real time and at scale. The Berlin-based startup was founded by CEO Namrata Sandhu and CTO Luca Schmid. In April 2022, the company closed an €11 million seed funding round led by Atomico with follow-on from CapitalT and participation from Seven Seven Six, along with a group of angel investors.
Vaayu leverages proprietary AI and machine learning technology to draw insights from a retailer’s production, sales, and logistics. The tool provides unparalleled, actionable insights into entire supply chains, empowering businesses to lower emissions and collectively reduce 1 gigaton of carbon emissions by 2030.
The solution integrates with point-of-sale and product life cycle management systems to calculate the carbon footprint of all daily transactions. While doing that, the software uses a database of more than 600,000 data points.
The retailers are provided with accurate and granular data on their operations, where their carbon emissions are the worst and, most importantly, where they should focus their efforts. As Sandhu said: “Previously, calculating carbon emissions has been complex and inaccurate, requiring businesses to manually pull out the data, which is time-consuming and inefficient. Vaayu’s AI and machine learning technology automatically calculates a retailer’s carbon emissions, making easy-to-use carbon data available in real-time, empowering them to measure and cut their carbon emissions in parallel to their business operations.”
The Norwegian startup was founded in 2020 by a team of geologists and data scientists: Jonas Aas Torland, Werner Svellingen, Helge Jørgensen and Rolf. M. Monsen. 7Analytics helps businesses and municipalities to plan and mitigate the impact of flooding. It’s last financial round (about €2.5 million) was closed in early September with the lead investment from Momentum, a Norwegian VC fund.
The company uses terrain processing, along with various other data sources, to combine flood models. Artificial intelligence and machine learning are an integral part of 7Analytics’s software solutions. Both technologies enable the software to achieve higher precision in data mining and analysis. As an example, the flood models provided by the startup are trained on historic flood events to increase the understanding of the parameters that control these events. The next chapter for the company is to use this insight to model other nature risks such as landslides and biodiversity.
“Understanding nature is an extremely complex process and it is, therefore, necessary to use robust and well-defined machine learning models – that can be trained from datasets across disciplines,” said Jonas Aas Torland, CCO at 7Analytics. “We are providing high precision tools to asset owners across the globe, so they can make mitigating actions to reduce damage during the next event.”
The London-based startup, founded by Mikela Druckman, Ambarish Mitra, and Nikola Sivacki, provides an AI waste analytics platform for the circular economy. The company uses AI computer vision systems, deployed globally in recycling facilities, to analyze and sort large waste flows at scale. Greyparrot announced a €10.2M Series A in May 2022.
Greyparrot’s live waste analytics dashboard equips waste managers, producers, and regulators with the insights they need to increase recycling rates and accountability across the waste value chain. The software uses computer vision — a form of AI that captures and analyzes images and video — to identify and categorize waste objects. The data is then sent to the waste analytics dashboard, which allows facility managers to accurately track and sort material with unprecedented visibility. Greyparrot AI vision, using API, can be integrated into third-party sorting machines and robots, allowing the industry to embed AI in the current infrastructure.
Machine learning turns the images captured into accurate data on the material type, brand, estimated weight, and volume of waste objects. AI scales the tracking and sorting process exponentially and provides nearly 100x the visibility of manual monitoring.
Greyparrot’s actionable insights increase the recovery of materials by 10 to 20%. Managers are able to guarantee the purity of their material with data, and charge more for it. The provided data also shows how “recyclable” certain products are and can be used to change packaging design for the better. The insights can be fed back to producers, who can then adjust the design methods with the recycling value chain in mind.
As for now, the company’s AI model has processed over 10B waste objects and can recognize over 50 categories of waste. The team is on track to increase this to over 100 categories in the next year.
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