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.
What does cloud, on-prem, and hybrid deployment mean here?
Flexible deployment allows the platform to run in public cloud, private cloud, on-premises, hybrid, or edge environments delivering the same analytics, simulation, and digital twin capabilities everywhere. Deployment choices are 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
Deploy intelligence where it makes sense—for today and tomorrow
Choose the deployment model that fits your operations now, and evolve as needs change.