GKN uses our technology to get more accurate classification of defects and to scale visual inspection quickly from one part to another and from one production line to many.
Alupress uses our technology to speed-up cycle times on complex parts by leveraging our 3D based machine learning approach. Furthermore, Alupress increases classification accuracy and saves costs.
No human required for lengthy, week-long programming of visual inspection systems. We leverage our unsupervised learning approach.
Higher detection rate compared to inspection by humans and traditional vision systems. Pseudo-scrap rate is reduced.
Defect detection learnings are transferred from one to many products on many production lines.
Our technology can be used to automate the end-of-line quality control process in various downstream industries that leverage non-ferrous metals such as aluminium, copper, and zinc as well as ferrous materials such as steel:
A team of experienced and visionary technology entrepreneurs works with best-in-class computer vision, artificial intelligence and machine learning researchers and engineers to disrupt the visual inspection market – starting with metals and plastics. We are currently looking for Computer Vision Engineers and Strategy and Business Development Interns.
Join our team by sending your resume to careers@covisionlab.com
