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System Modeling for Data Centers and AI Infrastructure
Data Center Reality Check and supporting system models
Assess a project's power, cooling, compute, permissions and financing as a connected system. See which conditions are supported by evidence, which remain uncertain and what a change could affect.
Commission a Reality Check independently or use it to ground a decision model. Existing engineering models and project data can be incorporated where they fit the scope.
Grounding the choices in the project
The parties' choices depend on what the systems can support
Consider a data center developer proposing a 120 MW campus with a 60 MW first phase. That first phase only works if the network, campus design and tenant demand support it. A system model makes those dependencies explicit.
- 01Establish the conditionsAvailable power, cooling capacity, equipment configuration and delivery evidence define which choices are feasible.
- 02Simulate the commitmentsCompare what happens when parties change the capacity, conditions or timing they will accept.
- 03Reassess as the system changesA delayed grid upgrade or a higher-density compute design can reopen earlier decisions.
A commitment is not a realized system change.
Signing for 60 MW changes the contractual position. It does not make 60 MW available. The models keep commitments, simulated effects and verified system conditions distinct.
System modeling
Data Center Reality Check
A model of the data center as a system of systems, presented through a top-level scorecard. See the project's conditions and dependencies, then examine the specific systems that could change the decision.
Project conditions behind the 60 MW path
Illustrative Reality Check view of the same scenario
Power
Conditional60 MW proposed initially. Network checks and connection milestones still need verification. A further 60 MW depends on an upgrade.
Cooling and compute
To verifyThe first-phase configuration must fit. Rack density, cooling capacity and equipment delivery need to support the tenant's workloads.
Permissions
To verifyApproval must cover the proposed configuration. A revised power or cooling design may change the conditions that apply.
Financing
ConditionalFunding follows verified milestones. A power-delivery delay can change when capital becomes available.
A change in any condition feeds back into the next decision and the scenarios worth exploring.
Commission a Reality Check independently or alongside decision modeling. Where suitable engineering models and project data already exist, use them to ground the decision model.
System models catalog
Explore the conditions that matter to your project
Start with the overall Reality Check, then go deeper where the decision needs it. These twelve modeling areas cover individual systems and cross-cutting assessments, from physical infrastructure to workload demand, economics and investment risk.
2 of 12 modeling areas · Semiconductors
To explore how parties decide under these conditions, visit the Decision models catalog or return to Solutions.
Supporting scorecard examples and related resources
Is this data center financeable?
Assess whether a named data center project is financeable, where evidence is thin, and which milestones should change terms.
View investor collateralIs this account worth pursuing?
Prioritize scarce pursuit, proposal, engineering, and equipment-window capacity across named campuses.
View pursuit collateralIs this load serviceable?
Check whether a claimed load is credible, phased, serviceable, and aligned with grid deliverability.
View load collateralCan this campus deliver?
Pressure-test commitments, schedules, counterparties, customer timing, and next milestones.
See operator use casesWhat are the public impacts?
Review power, water, emissions, land, permits, local response, and the tradeoffs behind public decisions.
Explore impact analysis
Model the systems your decision depends on
Request a Data Center Reality Check focused on your project, its dependencies and the evidence needed for the next commitment. Agree the depth of analysis, data integration and ongoing model maintenance with us.