Better, faster engineering.
Enter the era of AI-powered product data management.
Turning engineering conflicts into value-chain opportunities
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Manufacturing companies experience
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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
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Misses AI opportunities
The enterprise data being stuck in old databases, it makes it impossible to implement powerful AI projects
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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
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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