Enabling circular supply chains
Identify the source of recyclable materials and design an AI-driven waste collection
Artificial Intelligence can help bridge the data gap by modelling waste flows and designing cost-efficient and scalable waste logistics systems.

The data-driven planning will transform our supply chains to thrive in circular economies.
High costs of waste logistics and lack of waste management infrastructure in many areas on our planet significantly limit the supply of recycled materials.
Material suppliers and their waste collectors are facing two major logistics problems:
Fragmented and poor quality waste data is the main complication for the waste industry and sustainable manufacturers when planning the logistics of their waste commodity.
recyclable waste

Reducing costs of its reverse logistic
Waste Labs allowed us to significantly reduce the decision making risks and plan our e-waste collection with at least 10% less fleet and manpower.

Jakob Lambsdorf, CEO ALBA Singapore
Case Studies
Waste Labs is happy to share various case studies detailing our approach to the Circular economy. Each case study outlines the client's problem, the project steps, and the fantastic results we achieved.
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