HVAC Analytics

Predict service calls before they come in

AI-powered demand forecasting and technician routing for HVAC companies — built on real foot-traffic data, weather, and equipment age, not customer surveys.

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What HVAC companies deal with

Technicians drive across town for one call when three others are nearby — wasted hours every day
Seasonal demand swings catch you off guard — scrambling to hire in summer, idle trucks in spring
You know which neighborhoods generate the most calls, but you can't act on that data systematically

How we help HVAC operations

Service Demand Prediction

ML models trained on weather, geography, and equipment age to forecast service calls 2-4 weeks ahead.

Technician Routing

Optimized daily routes that minimize drive time and maximize billable hours per technician.

Service Area Heat Maps

Visualize call density, revenue per zone, and market penetration to focus your marketing spend.

Staffing Optimization

Predict seasonal demand peaks so you hire and train ahead of the rush, not during it.

Trade Area Analysis

Drive-time polygons and competitor proximity for territory planning and expansion.

Try the live foot-traffic lens

Rank neighborhoods and corridors by real visitor activity, weekday vs weekend patterns, and competitor density — the same dataset that powers HVAC demand forecasting.

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Real foot-traffic data from Foursquare + Overture Places — millions of US POIs, regularly refreshed

PostGIS, Mapbox, Python, TensorFlow, and custom ML forecasting models

Operated by Geospatial Solutions LLC — Washington, DC