Deploy the platform where your operations demand—cloud, on-prem, or hybrid

Run intelligent digital twins in the public cloud, private cloud, on-premises, or at the edge—without compromising security, performance, or capability.

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Definition

What does cloud, on-prem, and hybrid deployment mean here?

Flexible deployment means the platform can be deployed in public cloud, private cloud, on-premises, hybrid, or edge environments—while delivering the same analytics, simulation, and digital twin capabilities. Deployment choice is driven by operational, security, regulatory, and latency requirements—not platform limitations.

Operational systems don't live in one place

Unlike pure IT applications, operational environments face constraints such as:

  • Data that must stay on-site or within specific regions
  • Latency-sensitive use cases near machines or infrastructure
  • Strict security and compliance requirements
  • Limited or intermittent connectivity
  • Long system lifecycles and upgrade windows

A one-size-fits-all deployment model creates friction. Flexible deployment removes it.

Choose the model that fits your reality

Public cloud

Best for scalability and rapid expansion.

  • Elastic compute and storage
  • Centralized analytics and governance
  • Ideal for multi-site and global deployments

Private cloud

Balance control with cloud flexibility.

  • Dedicated environments
  • Greater isolation and governance
  • Common in regulated or sensitive industries

On-premises

Keep data and compute on site.

  • Full control over infrastructure
  • Meets strict data residency and security needs
  • Often used for OT-heavy or isolated environments

Hybrid

Combine on-prem and cloud strengths.

  • Sensitive ingestion stays local
  • Analytics and simulation scale centrally
  • Most common pattern for industrial and infrastructure use cases

Edge

Operate close to the source.

  • Low-latency processing
  • Resilience during connectivity loss
  • Complements central deployments

No feature trade-offs based on deployment

Regardless of where the platform runs, teams get:

  • The same analytics & ML capabilities
  • The same simulation engine
  • The same security and governance controls
  • The same APIs and integration patterns
  • The same accelerator library

Deployment choice affects where it runs—not what it can do.

Related capabilities:

How teams deploy in practice

Read-only OT, hybrid analytics

Ingest OT data on-prem, analyze and simulate in the cloud.

Phased modernization

Start on-prem for critical systems, expand to cloud over time.

Regional isolation

Deploy regionally to meet data residency and compliance needs.

Edge + central intelligence

Run local monitoring at the edge with centralized optimization.

These patterns allow teams to move forward without forcing infrastructure decisions prematurely.

When deployment adapts to the business

  • Faster approval from IT, OT, and security teams
  • Lower infrastructure and migration risk
  • Better performance for latency-sensitive use cases
  • Easier scaling across sites and regions
  • Future-proof architecture as requirements evolve

Flexible deployment ensures technology adapts to operations—not the other way around.

FAQ: Deployment options

Do we have to choose one deployment model forever?
No. Many organizations evolve from on-prem or hybrid to more cloud usage over time.
Is on-prem deployment fully supported?
Yes. On-prem deployments deliver the same core platform capabilities.
How does security change across deployments?
Security controls and governance are consistent across all models.
Can this work with limited connectivity?
Yes. Edge and hybrid deployments support intermittent connectivity scenarios.
Who manages the infrastructure?
Management responsibilities depend on the chosen deployment model and customer preference.

Deploy intelligence where it makes sense—for today and tomorrow

Choose the deployment model that fits your operations now, and evolve as needs change.

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