VIUN provides an AI-powered digital defect catalog that digitizes and standardizes quality inspection knowledge for manufacturing operations. This platform enables operators to collaborate efficiently and automatically trains custom visual inspection AI models directly from existing defect data. The system ensures full traceability of inspections while adapting continuously to evolving production standards and quality requirements.
Funding
Funding not disclosed
Founders
Product
Problem
Manufacturers often struggle with maintaining consistent quality standards in production processes due to reliance on manual visual inspections, leading to defects and increased costs. Traditional methods lack full traceability and can be inefficient in capturing and sharing quality knowledge across teams and factories.
Solution
The company offers an AI-powered defect catalog that enables manufacturers to achieve full traceability and reliable visual inspection of their production processes. The platform digitizes inspections, allowing operators to record and collaborate on defects efficiently. By leveraging this defect catalog, manufacturers can train AI models tailored to their specific quality standards, without requiring coding or AI expertise. The AI models adapt to evolving production and quality standards, performing consistently even in varying environments.
Target Audience
The primary target audience includes manufacturing operators, quality control teams, and managers in industries requiring visual inspection of parts and products.
Features
- Digital defect catalog for manufacturing operators to record and collaborate on defects.
- AI-powered inspection that learns directly from operator-labeled defect data.
- Full traceability of inspections to protect the organization's quality knowledge.
- Easy collaboration features to keep teams up-to-date with new defects and quality standards.
- Remote resolution capabilities for addressing quality issues across factories.
- Integrations with electronic microscopes and binocular devices via video or USB output.
- Integrations with Cognex, Keyence, Node-RED, MVTec, and SICK (coming soon).