Artificial Intelligence (AI)-equipped waste management robotics firm, Recycleye, has gathered US$17 million in funding during its recent financial drive.
Sorting various waste materials is extremely vital for a smooth recycling process. Recycleye optimises AI-run waste-extracting robots to reduce the cost of sorting material waste. The technology applies the smartness of a computer and high-end robotics to clasp and sort the materials without any hindrance.
With the AI protocol, the robot “sees” waste and has been formatted to pick materials like plastics, paper, cardboard and aluminium in a never-ending cycle.
Among all the mentioned waste materials, aluminium has the potential to be infinitely recycled without losing its original properties. Moreover, recycling aluminium releases lesser carbon into the air than primary aluminium production.
Recycleye’s AI technology focuses on transforming waste into useful raw materials, and also, it can generate important data propelling major decisions in the Material Recovery Facility.
The new investment will be essential for improving Recycleye’s sorting technique, boosting its uncommon accuracy.
The funding initiative was led by DCVC, with the already enlisted investors heightening their stakes. The existing players like Playfair Capital, Creator Fund, MMC Ventures, Promus Ventures and Atypical were all accompanied by new investors Seaya Andromeda, hailing from Madrid.
The first round of funding was US$5 million, essentially raised in 2021, while the second round amounted to US$2.6 million secured via the European and UK Government innovation fundraiser.
The Chief Technology Officer at Recycleye, Peter Hedley, exclaimed: “We believe that waste does not exist, only materials in the wrong place.”
“Our mission is to provide intelligent sorting technology that delivers dramatic financial and environmental returns to the global management of waste. This new investment will help us to further fine-tune our world-leading solutions, underpinned by the solid maintenance network our clients need to generate more output value,” Hedley added.
Responses
