Energy & Utilities
Sensor Intelligence detects grid anomalies, forecasts demand at four horizons, and gives operators an explicit confidence band on every forecast.
Built for utilities and grid operators who can't afford a “confidently wrong” model — and who need EU data residency by default.
SCADA feeds, smart meter telemetry, weather feeds, demand response signals.
Which substation will breach a threshold under the next cold snap. Which feeder shows pre-failure signature. Which forecast is least likely to underprovision.
Multi-horizon demand forecasts with confidence bands operators can use. Grid anomalies surface before they become outages. What-if simulation for switching decisions before you commit.
Where it lands
Distribution operators handle SCADA, smart meter, weather, and demand-response signals at a scale where threshold alarms produce more false positives than real signal. The cost of a confidently wrong forecast — overprovisioning under-load, or underprovisioning a cold snap — runs into operational risk, not just headcount.
Forecasting with explicit confidence bounds replaces point estimates that pretend to be precise. Anomaly detection across six methods surfaces pre-failure signatures on substations and feeders, and causal filtering kills the alarm storms that come with a single upstream change.
Built for
Operations, planning, and asset-management leads at DSOs, TSOs, district-energy operators, and large industrial energy consumers.
What changes
Worked example
A regional DSO reduced false-positive substation alarms by 84% in the first quarter by replacing threshold alarms with the classified, ranked queue. The team stopped chasing transients and started fixing the ones that mattered.
Regulatory & compliance notes
Aligned with EU energy efficiency reporting and ISO 50001 evidence collection.
20-minute demo, scoped to energy & utilities. Senior engineer on the call.