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See the operating envelope
- Real-time power monitoring
- Peak-demand prediction
- Grid-stress alerts
- Grid-capacity forecasting
Capacity optimization for AI infrastructure
GridFlexAi turns power telemetry, workload flexibility, and grid signals into a safer capacity plan—so data center operators can make the next compute decision with context.
Planning recommendations only. Operators approve every workload or battery action.
North corridor · sample data
Capacity horizon
Forecast peak
42.8 MW
18:30 local
Flexible queue
3.6 MW
Policy-approved
Recommendation: move two flexible training queues by 90 minutes to preserve a 2.1 MW operating buffer.
The capacity problem
01
Power operations and compute scheduling plan around different signals.
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Peak risk can strand useful capacity before an expansion is ready.
03
Utilities need a credible view of flexible load—not a late surprise.
One planning system
A single operating language connects the power you have, the work you can move, and the capacity decision ahead.
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Two-sided coordination
GridFlexAi gives data center operators a practical way to model flexible load while giving utility teams a consistent coordination view. Each team retains its own controls and data boundaries.
Data center teams
See planned peaks, eligible workloads, site constraints, and expansion scenarios.
Utility partners
Receive structured flexibility reporting and a shared view of planning assumptions.
Coordination signal · sample
Utility outlook
Moderate stressFacility flexibility
3.6 MW eligible across two policy-approved queues
Shared planning window
18:00–20:00 local · recommendation ready for operator review
Capacity becomes a conversation, not an incident.
Demoable workflows
Start with the capacity you have
Tell us about the facility decision in front of you. We’ll use that context to frame a planning conversation—not a generic demo.
Peak and flexibility planning
Battery and site-routing scenarios
Utility coordination readiness