AI Vegetation Risk Management
Analyzes LiDAR, imagery, and outage history to prioritize vegetation trimming and reduce vegetation-related faults and wildfire risk.
The Problem
“Prevent vegetation-caused outages and wildfire ignitions”
Organizations face these key challenges:
Limited visibility between inspection cycles leads to missed hazards and reactive emergency work
Manual prioritization cannot consistently account for local growth rates, microclimates, and storm-driven risk across millions of spans
Compliance documentation and audit readiness are fragmented across contractors, work orders, and GIS, increasing regulatory exposure
Impact When Solved
The Shift
Real-World Use Cases
AI in Energy Industry: Smart Grid Optimization and Energy Management
This is like giving the entire power system—power plants, grids, and large customers—a real‑time ‘autopilot’ that constantly predicts demand, reroutes electricity, and tunes equipment so you use less fuel, waste less energy, and keep the lights on more reliably.
AI Grid Congestion Management
This AI helps optimize the layout of power grids to reduce congestion without increasing costs or carbon emissions.