Veolia Australia Deploys EverestLabs' AI-Powered Recycling Robotics

Aug 29, 2025
Veolia Australia has partnered with EverestLabs to implement AI-driven recycling robotics at its Perth facility, enhancing sorting accuracy and recovery rates.

Veolia Australia has partnered with EverestLabs to deploy AI-powered recycling robotics at its material recovery facility in Perth, marking the first international deployment of this technology. Announced in a press release, the initiative aims to digitize and automate sorting operations, significantly improving sorting accuracy and recovery rates.

The deployment of EverestLabs' modular vision AI and robotic sorting solution provides Veolia with real-time visibility into plant operations, addressing labor challenges and increasing material recovery rates. Each robotic cell is equipped with vision AI that identifies recyclable materials in real time, directing robotic arms to sort items with a 90% pick success rate, operating 2-3 times faster than manual sorting.

This collaboration is part of Veolia's broader commitment to modernizing recycling infrastructure and improving circular outcomes through innovation. EverestLabs' RecycleOS™ solution was chosen for its turnkey deployment model and ability to integrate seamlessly into existing infrastructure, enhancing operational efficiency and safety by reducing the need for human workers in hazardous zones.

We hope you enjoyed this article

Consider subscribing to one of our newsletters like Robotics Brief or Daily AI Brief.

Also, consider following us on social media:

AI & Robotics AI Brief AI Brief (X)
Free newsletter

Robotics Brief

Weekly coverage of AI-driven robotics advances in industrial automation, autonomous vehicles, and robotic systems.

AI Token Webinar

Whitepaper

Tensordyne Napier: What If One Rack Could Do the Work of Nine?

Tensordyne

This Tensordyne whitepaper presents Napier, an inference-focused AI processor and rack-scale system based on the company’s TDN Math logarithmic number system. It examines infrastructure requirements for large mixture-of-experts and agentic models, compares major inference architecture approaches, and details the TDN AIP processor, TDN72 pod, TDN Link fabric, and Napier Ultra configuration. The paper reports simulation-based performance, cost, and accuracy-validation results, including Tensordyne’s projected comparison of one Napier rack with a nine-rack Nvidia Rubin plus Groq deployment; the chip is reported as taped out and in fabrication.

Read more

You may also like

Free, six days a week

Daily AI Brief: the AI news that matters, in your inbox.