About GeoGridIQ
GeoGridIQ is a self-funded project built by Justin St-Laurent to explore how GIS, AI, weather intelligence, and operational analytics can help utilities move from outage response to outage prevention.
GeoGridIQ was created by Justin St-Laurent, a technology enthusiast focused on practical systems, data, automation, and operational decision-making. The project grew from a belief that outage data, weather, GIS, and analytics can be combined into clearer intelligence for real-world infrastructure work.
Most outage workflows begin after disruption is already visible. GeoGridIQ was built to test a more proactive approach: identify risk signals earlier, explain why they matter, and help teams prepare before conditions escalate.
Utilities face storms, vegetation pressure, aging infrastructure, critical asset exposure, and limited crew capacity. These challenges require fast interpretation of geospatial, environmental, historical, and operational data.
The project reflects a passion for applying GIS, AI, weather intelligence, model validation, and operational analytics to problems where better context can support better preparation.
Frequently asked questions
GeoGridIQ was built by Justin St-Laurent as a self-funded technology and operational intelligence project.
It was created to explore how GIS, AI, weather intelligence, and operational analytics can help utilities move from outage response toward outage prevention.
No. GeoGridIQ is a decision-support and intelligence platform project, not a utility operator.
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Related GeoGridIQ resources
Read GeoGridIQ documentation for platform overview, data sources, prediction engine, GIS engine, weather intelligence, NDVI, and crew optimization.
Public utility intelligence reports covering Quebec outage risk, vegetation threats, storm impact, and critical infrastructure exposure.
GeoGridIQ helps utilities forecast outage risk using weather intelligence, vegetation analytics, historical outages, GIS context, and model confidence scoring.
Monitor vegetation outage risk with NDVI analysis, satellite context, GIS layers, and utility risk scoring.