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Where It Runs

Deployment Models

Cloud, hybrid, on-premise, air-gapped, and sovereign deployments — with the trade-offs, industries, and controls that shape each choice.

Last updated Version 2.4

One architecture, many environments

The same Institutional Intelligence Architecture runs across a spectrum of trust and residency requirements. The deployment model changes where data lives and who operates the environment — it does not change the layers above it. That separation is what lets security posture evolve without an application rewrite.

Compare deployment models

Select a model to see its data residency, latency, control posture, ideal use cases, trade-offs, and the industries that most often adopt it.

Hybrid

Sensitive data and inference stay local; scale bursts to cloud.

Data Residency

Sensitive tiers on-premise, elastic tiers in cloud

Latency

Local for critical paths, elastic for the rest

Control

Organization retains control of the sensitive tier

Best for

  • Mixed sensitivity
  • Gradual migration
  • Cost/performance balance

Trade-offs

The most flexible model. Requires clear data classification so the split between local and cloud tiers stays principled.

Common inManufacturingIndustrial Operations

How to choose

Start from the most sensitive data the system must reason over and the regulatory boundary it sits within. That constraint sets the floor: classified or export-controlled data points to air-gapped or sovereign; strict national residency points to sovereign; existing data-center investment and OT proximity favor on-premise or hybrid; and where residency can be met contractually, managed cloud offers the fastest path to value. Most organizations land on hybrid, keeping sensitive tiers local while bursting elastic workloads to the cloud.