What We Do
Vertocube supports cities, regional districts, municipalities, and intermunicipal boards in designing and deploying smart collection and incentive-based pricing systems also named “Pay-as-you-throw (PAYT)”— backed by a decade of municipal practice and an independent technology platform.
Collaborative Approach
Vertocube’s development is part of an innovation ecosystem bringing together municipalities, public bodies, research centres, and technology partners.
Several organizations have contributed to the evolution of these projects and to the thinking around smart collection and incentive-based pricing.
These collaborations have made it possible to test, document, and refine smart collection and incentive-based pricing approaches across a range of municipal contexts.
- City of Beaconsfield
- City of Lorraine
- City of Gatineau
- City of Montréal — Environment Department and Saint-Laurent Borough
- Récolo (Portneuf intermunicipal residual materials management board)
- City of Québec
- City of Laval
- Gaspésie intermunicipal residual materials treatment board
An independent platform for municipal waste collection data
For more than a decade, Vertocube has supported Quebec municipalities and intermunicipal boards in deploying smart-collection and incentive-based pricing projects. Every project surfaced the same blocker — waste-collection data was fragmented across operators, vendor portals, and spreadsheets, and the tools to consolidate them were not designed for public ownership.
BinLogiQ was built to change that. One independent platform that turns operator data into municipal decisions — on carts, costs, pricing, and waste reduction targets.
More than ten years in municipal smart collection
BinLogiQ grew out of more than ten years of work by EnviroRcube, the organization that has supported over twenty municipalities in their way toward deploying smart collection with or without incentive- based pricing projects.
That field experience identified a major obstacle: despite interest in these approaches, the data analysis for cart assignment is still too time-consuming due to fragmented and unintegrated data.