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Mergen named ServiceNow Elite Partner and Center of Excellence of the Year

Measured outcomes

What this programme actually delivered.

+28%

Forecast accuracy: +28% across substations

$11M

$11M annual savings on excess capacity reservation

The challenge

A regional utility forecast electricity demand at the regional level using historical patterns + weather. Substation-level forecasts didn’t exist; grid-balancing was reactive.

What we built

ML-based forecasting at the substation level (1,400+ models). Features include historical demand, weather, calendar, distributed-energy-resource production, and EV-charging patterns. Continuous retraining.

Outcomes

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