Recycleye develops AI-powered robotic sorting systems that enhance waste management operations by accurately identifying and separating various materials, including plastics and metals. This technology improves the purity of recyclables and reduces operational costs by minimizing labor requirements and increasing sorting efficiency.
Funding
$23.6M raised to dateRaised to date based on public sources. This may differ from the amount the company actually raised and is based only on what is publicly available on the internet.
Founders
Product
Problem
Waste management facilities face challenges in accurately sorting recyclable materials due to the variability and complexity of waste streams. Manual sorting is labor-intensive and prone to errors, while traditional sorting technologies often lack the precision needed to achieve high purity levels. These inefficiencies lead to reduced profitability and lower-quality recycled outputs.
Solution
Recycleye provides AI-powered robotic sorting solutions designed to improve the efficiency and accuracy of waste management operations. Their systems use advanced computer vision to identify and separate various materials, including plastics, metals, fiber, and WEEE (Waste Electrical and Electronic Equipment), with a high degree of precision. By automating the sorting process, Recycleye helps facilities increase the volume and purity of recyclables, reduce labor costs, and optimize overall operational performance. The retrofittable robots can be integrated into existing sorting lines, providing a scalable solution for enhancing material recovery and resource efficiency.
Target Audience
Recycleye's primary customers include waste management companies, recycling facilities, and MRFs seeking to improve sorting efficiency, increase material purity, and reduce operational costs.
Features
- AI-powered computer vision system capable of identifying a wide range of waste materials, including plastics, metals, fiber, cartons and WEEE.
- Robotic arms with high-speed picking capabilities, enabling efficient removal of target materials from the waste stream.
- Real-time data analytics and KPI dashboards for monitoring sorting performance, material volumes, and purity levels.
- Retrofittable design for easy integration into existing material recovery facilities (MRFs) with minimal disruption.
- AI-powered optical sorters that use air jets for material ejection.
- Ability to sort materials based on visual features, rather than purely color and light-based sensors.
- Solutions for quality control, optical sorting, and data insights.