Better, faster engineering.
Enter the era of AI-powered product data management.
Turning engineering conflicts into value-chain opportunities
Manufacturing companies experience
Long and costly engineering
Launching new product or optimising product portfolio is a loing and costly process because legacy systems (CAD, ERP, PLM) fail to reconcile product data
Misses AI opportunities
The enterprise data being stuck in old databases, it makes it impossible to implement powerful AI projects
No e2e Value-chain information
Information through the value chain is lost. Then follow compliance, quality and procurement issues
Join the innovators
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Tesla
Tesla custom developed an end-to-end Product structure platform to enable the ramp-up for the Model 3
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Michelin
Michelin created the knowledge graph to allow unification of R&D (material) and Engineering data for hybrid development with AI
Us army
The US Army could not stand its slow and inflexible PLM and BOM. So it built a data layer on top of its system to unleash AI capabilities on their equipments
