Overview
What this module delivers
The Cloud module gives teams a controlled workspace for models, geometry, validation evidence, and review artifacts, with tenant isolation, role-based access, and traceable project history.
Capability focus
Inputs
Projects, models, geometry, validation evidence, user roles, and collaboration scope.
Outputs
Versioned milestone snapshots, expiring review links, controlled project sharing, and traceable approval history.
Guardrails
Tenant isolation, role-based access, regional handling options, and governance aligned to customer collaboration requirements.
Deep dive
Functionality
Controlled workspaces organize project artifacts in one place: models, geometry, validation evidence, and cross-team review materials, so distributed reviewers see consistent context instead of ad hoc file drops.
Version lineage ties updates to milestone snapshots and checkpoints, improving change traceability when engineering, quality, and OEM stakeholders review the same nanocrystalline core program from different regions.
Secure sharing uses access policies and time-bound review links so external participants receive only the scope they need. Regional handling options can be aligned to program policy, and enterprise buyers can discuss hybrid or otherwise governed environments during procurement and technical review.
Evaluation dimensions
- Workspace isolation and roles
- Version and milestone traceability
- External sharing scope and expiry
- Regional or hybrid governance fit
- Audit history for approvals
Example workflow
An India manufacturing team, a Canada sales engineering lead, and a US OEM reviewer work inside a shared project space with role-based permissions, milestone snapshots, expiring review links, and a traceable audit history for approval gates.
Use the links below for the CoreMagna AI hub, adjacent modules, and CenturaCores tools and product context that fit your program.
- CoreMagna AI hub
- CoreMagna AI Insights module for portfolio and program signals
- CoreMagna AI Design module for constraint-aware core geometry
- CoreMagna AI Simulation module for electromagnetic behavior review
- CoreMagna AI Application module for review packets and guardrails
- CenturaCores privacy policy for data handling disclosure
- CenturaCores quality assurance programs and evidence expectations
Advantages
Less email-driven version confusion across distributed teams
Better control of IP exposure during OEM collaboration
Clearer traceability for approval and design-review history
More consistent governance across regional and customer-specific workflows
Target users
- IT and security stakeholders reviewing collaboration tooling
- Distributed engineering teams managing controlled project access
- OEM and partner teams participating in secure review cycles
Industry use cases
- Global EV programs coordinating multi-site design and validation reviews
- Solar OEMs collaborating across supplier, factory, and engineering teams
- Medical device partnerships operating under strict document and access controls
Ready to explore CoreMagna AI?
Join the beta or speak with a nanocrystalline specialist about your program requirements and validation path.
Frequently asked questions
What security controls are available?
Tenant isolation and role-based access define who can view or change project workspaces. Programs can use milestone snapshots, expiring review links, and traceable approval-oriented history to support review discipline. Regional handling options can be aligned when collaboration policy requires it.
Can hybrid or customer-governed deployments be discussed?
Yes. Enterprise procurement and security reviews can include discussion of hybrid or customer-governed deployment models based on your requirements. The agreed operating model is defined during scoping rather than assumed as a default.
How is version history represented?
Version history is anchored to milestone snapshots that collect models, geometry, and validation evidence at reviewed checkpoints, so teams can compare what changed across iterations and approvals.
Can access be restricted by role or regional handling requirements?
Yes. Access is managed with role-based permissions, and regional handling approaches can be matched to customer collaboration policies when those requirements apply to the program.
Which CoreMagna AI modules produce artifacts that belong in Cloud workspaces?
Typical artifacts include geometry and model exports, validation evidence, correlation summaries, review packets, and milestone snapshots associated with Design, Simulation, Loss, Material, and Application workflows. Exact retention follows your governance policy.