What this fixes.
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Location decisions made on gut + ZIP-code aggregates
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Field surveys expensive and stale
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No baseline for risk pricing by parcel
Three jobs, on rails.
Multi-source
Satellite imagery + foot traffic + parcel maps.
Per location
Decision-ready scores per use case (OOH / agri / risk).
Self-serve
Interactive map layer for non-technical users.
The path.
Pick the use case (OOH placement, agri yield, peril exposure, etc.) — that's the scoring rubric.
Pull the inputs: satellite imagery, foot traffic, parcels, your portfolio.
Calibrate scoring against 30–50 historical examples the business has opinions about.
Serve the map layer to the operators — planners, underwriters, leasing teams.
One scenario, one outcome.
An insurance carrier needs to repriced a 12,000-property book ahead of wildfire season.
Each parcel gets a peril score in under 24 hours. The 8% high-risk tail is re-priced or non-renewed; the rest stays put. Loss-ratio expectation drops from 71 to 58.
Scoped on a call.
6 weeks
Pilot → retainer
Scope confirmed in a 30-minute call. Fixed scope, fixed timeline before you sign. We'll send a one-page proposal within 48 hours.
Book a call →Same category.
Demand Forecasting
ML forecasts on sales, promo, weather and macro signals — cuts inventory carry and stockouts simultaneously.
Predictive Maintenance
IoT + ML predicts equipment failure days or weeks ahead — turns unplanned downtime into planned maintenance.
Computer Vision QC
Camera + vision model inspects every unit on the line — catches defects sampling misses.