Making
Recycling
Work.

Demo →

Insecurity and complexity make recycling systems tough to orchestrate. Recycling networks behave like living systems. Volumes fluctuate, quality varies, partners act independently, and constraints shift over time. This complexity creates insecurity in planning and day-to-day decisions. The result is predictable: utilisation stays too low, economies of scale don't materialise, and unit costs rise until the system becomes economically fragile.

Our software helps by providing data-driven forecasting, optimisation, and decision-making. MESH provides a Planning & Operations System that turns fragmented data into a shared information platform. It forecasts supply, optimises the network configuration, stress-tests scenarios, and supports daily allocation decisions so recycling systems reach stable throughput, lower unit costs, and reliably deliver circularity targets.

Planning

Forecast where usable material will come from

See where, when, and how much construction waste is likely to become capturable and usable input before you invest or commit to targets.

Test scenarios and find the real levers

Model changes (new hubs, tighter specs, higher sorting depth, contract shifts) and run sensitivity analyses to understand which variables truly drive cost, utilisation, and recycled-content feasibility.

Track assumptions and keep the model honest

Make assumptions explicit, versioned, and measurable, then compare them to real data over time to detect drift and improve forecasting accuracy.

Planning OS forecast demo

Operations

A live cockpit for capacity and circular KPIs

Monitor utilisation, backlog, service levels, recycling rate, recycled content, and rejects across the network so issues are visible before they become expensive.

Daily allocation decision support

For each incoming load, evaluate routing options and choose the best destination based on cost, service, quality risk, and impact on recycled-content targets.

Dynamic acceptance pricing

Align incentives with reality by dynamically adapting acceptance pricing to capacity, demand, and quality, securing volumes without destroying margins.

Operations OS allocation demo
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