Recycleye Secures £3.5M Seed Funding to Accelerate Efforts Towards Global Waste Epidemic
Do you ever wonder where your recyclables go after it’s been collected by your local waste management department? The world has been proactively seeking new ways to improve its waste management capabilities in efforts to create a sustainable environment for the foreseeable future.
At present, the world produces over 200 billion tonnes of waste per year, with over 300 million tonnes belonging solely to plastic waste. So how does the world sort the sheer amount of rubbish we produce every year? The answer lies in tech-driven solutions focused on artificial intelligence (AI) and robotics.
Recycleye: Sorting the World’s Waste
Founded in 2019, Recycleye is a London-based tech startup that focuses on combining AI, robotics, and advanced machine learning software to sort out global waste in an efficient and sustainable manner.
The company recently secured a seed funding of £3.5M from deep-tech venture capital firm, Promus Ventures through its Orbital Ventures space fund, along with existing investors Playfair Capital, MMC Ventures, Atypical Ventures, and Creator Fund.
Adding to the support from Biffa and ReGen in United Kingdon (UK), along with three of the five leading waste management companies in Europe, its recent funding enables the firm to pour its efforts into enhancing the accuracy, scope, and capabilities of its machine learning and robotics technology.
The company is also set on expanding its reach to new European territories, while strengthening existing partnerships in the UK, France, and Italy.
Integrating AI and Machine Learning into Waste Management
Recycleye integrates AI and advanced machine learning into material recovery facilities and waste management systems, allowing the industry to further its sorting capabilities. Their team of research engineers developed automated turnkey solutions, utilizing their extensive visual database of waste items and low-cost robotics.
The company also partnered with leading universities to develop WasteNet, the world’s largest dataset containing over 2.7 million training images created by deep learning and computer vision. These datasets are then refined by weight and brand-level detection using Recycleye’s vision system, allowing MRFs to efficiently and accurately sort recyclables.
Their extensive AI and machine learning capabilities teach powerful recycling robots to prevent valuable recyclates from being downcycled while eliminating the factor of dangerous manual labor. The tech houses brand-level waste, synthetic waste, and object and material-level waste detection in lab and industry settings.
The company also provides a Smart Analytics Platform, allowing waste management companies to fully monitor their MRFs’ performance, trend analysis, and total waste stream knowledge to help optimize material recovery throughput.
Photo credit: Recycleye | Object and Material-Level Detection
Spearheading the Green Revolution
Founders Victor Dewulf and Peter Hedley started Recycleye in 2019 in Bournemouth, England. With extensive international industry experience, Recycleye Chief Executive Officer (CEO) Dewulf gained his Master of Sciences (MSc) in Environmental Engineering in Business Management from Imperial College London. Currently, he is finishing his Ph.D. in Waste Management at the same university.
Hedley, the Chief Technology Officer of Recycleye, also gained his Masters in Computer Science at Imperial London College. He is responsible for the company’s tech strategy and the overall development and dissemination of Recycleye’s solutions.
Recycleye also has a large team of industry professionals committed to accelerating the world’s transition to the circular economy.
The Future of Waste Management
By combining advanced AI and machine learning with powerful low-cost robotics, the world can take a step closer to achieving a more sustainable way of sorting its rubbish, segregating it in its proper place.
Efforts from numerous public and private organizations, such as Recycleye, allow us to innovate and find better and greener solutions to the global waste problem.