Our vision is to disrupt the status quo by building an AI-driven recycling ecosystem that transforms waste into a dynamic, profit-generating asset. Our AI-driven solution redefines the entire recycling value chain, unlocking real economic value from waste.
Our holistic solution tackles the recycling challenge from end-users to producers. By integrating advanced AI into a seamless, data-centric network, we transform waste management into a high-value, circular economy. This unified system redefines recycling as a strategic driver of sustainable innovation and profitability, connecting every stakeholder through real-time insights and continuous optimization.
Introducing cutting-edge AI technology to existing production lines, automating quality inspection of targets to ensure sorting purity and maximize re-use value for your factory.
Enhance processing capacity and purity, reduce labor burden, and lower operational costs. We strive to increase your profitability with powerful technology to unlock more opportunities.
Providing a data-science-based intelligent recycling facility management system, using visualization to make factory operations clear at a glance.
The recycling industry faces growing challenges from labor shortages and hazardous working conditions. AI-powered recycling offers a solution by automating sorting, improving efficiency, and enhancing worker safety. How will this technology transform the industry and drive sustainability?
Jiun-Ling Wei
Data Annotation Team Leader
Traditional recycling methods, reliant on manual labor and subjective judgment, struggle to meet the demands of modern waste management. With the rise of Artificial Intelligence (AI), the recycling process becomes more precise and efficient, driving the realization of a circular economy and creating lasting value for the planet's future.
Chieh-Han Lee
CTO
Traditional waste dataset collection has limitations, such as imbalanced data and labeling errors. AIRECO's synthetic data generation method addresses these challenges by using 3D models to simulate waste, improving data quality and scalability. Learn how this approach enhances AI training and reduces human effort.
Rémi Pyronnet
Computer Vision Engineer
