Viridium AI offers a Science‑AI platform that ingests structured and unstructured product data from ERP, PLM, MES and documents, enriches bill‑of‑materials, and creates a trusted digital product twin linking products, parts, chemicals and suppliers. The system continuously maps materials to regulatory definitions at the molecular level and provides real‑time compliance, supplier risk and tariff exposure analytics, turning weeks of manual reconciliation into minutes.
Funding
Funding not disclosed
Founders
Product
Problem
Manufacturers struggle to obtain a unified, accurate view of material composition, regulatory compliance, and supplier risk because product data is scattered across ERP, PLM, MES, and unstructured documents, making manual reconciliation time‑consuming and error‑prone.
Solution
Viridium AI provides a “Science‑AI” platform that ingests product data from any source, enriches bill‑of‑materials with missing part and material details, and creates a trusted digital product twin linking products, parts, chemicals, and suppliers. The system continuously maps materials to regulatory definitions at the molecular level, delivering instant impact assessments for compliance and sustainability reporting. By automating chemical intelligence, the platform highlights margin‑impacting tariff exposures and identifies high‑risk suppliers, enabling faster, data‑driven decision‑making across the value chain. Its AI models are built on finance‑grade data engineering with human‑in‑the‑loop validation to ensure traceable, physics‑based insights. Users can query the integrated knowledge base through an intuitive interface, reducing weeks of manual work to minutes.
Target Audience
Primary customers are large manufacturers in discrete, medical device, and industrial sectors that need comprehensive material compliance, risk management, and cost‑optimization across complex product portfolios.
Features
- Automated ingestion of structured and unstructured product data from ERP, PLM, MES, and documents
- Enrichment of BOMs with missing part and material attributes using purpose‑built Science‑AI
- Chemical intelligence engine that maps materials to regulatory definitions and molecular structures for real‑time compliance checks
- Supplier risk and tariff exposure analytics that surface margin‑impacting insights
- Digital product twin that connects products, parts, chemicals, and suppliers for end‑to‑end traceability
- Human‑in‑the‑loop validation ensuring AI recommendations are auditable and physics‑aligned
- Scalable cloud architecture supporting large product portfolios and multi‑site data sources