Predictive Analytics

Predict demand. Optimize operations.

AI-powered forecasting and automation for logistics, retail, and field-service teams that need to plan ahead, not react — built on real foot-traffic data, not survey estimates.

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Why operations teams need predictive analytics

You're reacting to demand instead of anticipating it — overstaffing some days, understaffing others
Spreadsheet-based forecasting can't account for spatial patterns, weather, or seasonal shifts
Your competitors are using AI-powered foot-traffic and demand models — every month you wait, the gap grows

What we build

Demand Forecasting

ML models that predict service demand by location, time, and customer segment — using real foot-traffic data, not surveys.

Spatial Analytics

Geographic clustering, hotspot analysis, and territory optimization for field operations.

Process Automation

Automated scheduling, resource allocation, and dispatch based on predicted demand.

Performance Dashboards

Real-time KPI tracking with predictive indicators and anomaly detection.

Territory Optimization

Drive-time polygons and trade-area analysis to minimize overlap and maximize coverage.

Try the live foot-traffic lens

Rank every business in a neighborhood by real-world visitor activity — corner activity, competitor proximity, weekday vs weekend patterns.

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Foursquare popularity + Overture Places — millions of US POIs, regularly refreshed

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

Operated by Geospatial Solutions LLC — Washington, DC