
Production
Achieve greenfield manufacturing with Agentic EI in Production
Increasing innovation, customization and digitalization also increases the challenges of maintaining high quality and efficiency in series production. Engineers need to design ideal production processes while considering hundreds of constraints and correcting errors as early as possible to avoid quality issues and recalls.
Explore our use casesTake a look at how SPREAD can help you find and fix production errors faster and produce even more efficiently and with higher quality.
Production
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Design production-ready system architectures
Design production-ready system architectures
All Domains

Product Architect
Determine and optimize assembly steps using algorithm-based priority graphs based on the geometry of 3D CAD models.

Guide E/E troubleshooting for improved first-pass yields
Guide E/E troubleshooting for improved first-pass yields
All Domains
E/E Inspector
Link errors in production to system dependencies for faster resolution of E/E issues. Enable teams to uncover root causes, reduce downtime and increase first-pass yields.

Provide live product knowledge and guidance
Provide live product knowledge and guidance
All Domains
Upskilling Coach
Deliver live access to product knowledge, variant-specific data, and actionable guidelines. Enable teams to adapt quickly to complex and new products, while maintaining performance on the shop floor.

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Build your own applications
Cross-functional product knowledge is just a few clicks away
Get fact-based insights for any use case. Easily build custom apps within minutes in our low-code SPREAD Studio. Simply connect your data and choose from a variety of interfaces, pre-built widgets, and tailored analyses for your domain-specific needs.
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Get to know the solution
French National Railways meets SPREAD: How Digital Twins and unified product data redefine rail operations
Modern high-speed trains are complex data ecosystems. Each new-generation train can contain over 300,000 components and up to 20 million lines of code, generating dozens of gigabytes of data daily. For railway companies like SNCF Voyageurs – which reports serving close to 10 million passengers every day – this technological leap heightens the challenge to balance operational reliability, sustainability, and soaring passenger expectations.
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