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recyclable scrap metal

VALIS

Global Problem

Technological advancements and a growing global population are increasing material consumption at a rapid rate.  Scrap metal current practices are unable to maximize material value recovery, meet increasing consumer specifications, or adjust sorting criteria in real time as markets shift.

Our Solution

VALIS is a machine learning model fed by multiple critical data streams to make more intelligent and optimized sorting decisions with guaranteed profitability and quality. We aim to will develop the first real-time adaptive sortation algorithm introduced to the non-ferrous scrap sortation industry.

Specific Activities

Solvus Global has been awarded an NSF SBIR Phase 1 grant to develop an artificial intelligence algorithm to support the advancement of scrap metal sorting. 

Current Status

Embarking into NSF SBIR Phase II, VALIS seeks to complete integration, testing, and commercial-scale optimization of the VALIS software-hardware package with sensor-sorting systems.

Expected Impact

VALIS will enable domestic scrap processors to become more competitive within the material supply chain by giving them the ability to adapt, in real-time, to an ever-changing material consumption climate. By bringing value and intelligence to the world of recycling, VALIS can completely automate scrap sortation for the next generation.