Outage reduction from predictive maintenance on transmission and distribution assets.
ROI from non-critical-asset predictive maintenance with 6–9 month deployment.
Margin improvement from AI-optimized energy trading and dispatch.
Achieve immediate, organization-wide results
Six measurable outcomes across grid reliability, wildfire risk management, demand forecasting, and field operations, deployed in months rather than years.
Asset Failure Prediction
Transformer, turbine, and substation failure prediction from sensor + thermal + maintenance history. 25–40% fewer outages.
Wildfire Risk Modeling
Computer vision + LiDAR + weather to score ignition risk per circuit. National Grid and Western IOUs already running this in production.
EV Charging & Load Forecasting
Per-feeder load models that integrate EV adoption, heat-pump rollout, and demand-response enrollment.
Grid Optimization & Dispatch
Power flow, congestion, and DER orchestration with reinforcement learning. 8–15% margin uplift on energy trading.
Outage Prediction & Storm Response
Pre-storm circuit risk scoring fused with crew-dispatch optimization for faster restoration.
Regulatory & R&D Research AI
RAG-grounded research-AI over FERC orders, PUC filings, NERC standards, IRENA reports, and your internal regulatory + renewable-tech research library. CSRD / IFRS S2 emissions reporting included.
Capabilities across the energy & utilities value chain
Grid Reliability & Asset Health
- Transformer, turbine, and substation failure prediction
- Vegetation-encroachment vision from satellite and LiDAR
- Battery and renewable-asset performance modeling
- DER (BESS, solar, EV) coordination and aggregation
Wildfire & Risk Management
- Ignition-risk scoring per circuit and pole
- PSPS (Public Safety Power Shutoff) decision support
- Drone imagery and thermal-anomaly detection
- Storm-impact prediction and crew pre-positioning
Demand Forecasting & Trading
- Per-feeder load forecasting with EV, heat-pump, and DR signals
- Day-ahead and intraday energy-market trading models
- Renewable-output forecasting (solar, wind) with ensemble methods
- Congestion and locational-marginal-price prediction
Customer & Field Operations
- Outage-call classification and crew routing
- Meter anomaly and revenue-protection scoring
- Customer-segment energy-program targeting (DR, EE, EV)
- Worker-safety vision and PPE compliance monitoring
How a Western IOU cut wildfire-driven PSPS hours 38% with circuit-level risk scoring
A Western U.S. investor-owned utility was triggering 12-day PSPS events annually that affected 500,000+ customers and triggered regulator scrutiny. We built a circuit-level wildfire risk scoring model that fused weather forecasts (NOAA HRRR), vegetation health (multispectral satellite), historical ignition data, and live asset health from SCADA telemetry. PSPS-hour exposure dropped 38% within one fire season, and the regulator-facing risk-spend prioritization freed up $22M in capital that was being spent on lower-risk circuits. The same vegetation models now drive a 5-year trim-cycle plan that reduces vegetation-caused outages by 45%.
Speak with an energy & utilities AI expert
A 45-minute scoping call. We come prepared with your asset base, your generation and network data, and a directional read on which workflows are worth automating first.
Ask us about
- Transformer and substation failure prediction
- Wildfire ignition-risk scoring per circuit
- EV and heat-pump load forecasting per feeder
- DER and battery-storage orchestration
- Energy-trading and renewable-output models
- Regulatory and renewables research-AI (incl. CSRD / IFRS S2 emissions reporting)
Frequently asked questions
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Ready to talk energy & utilities AI?
Start with a 45-minute strategy session. We come prepared with a directional read on your operation and a scoped proposal.