What this fixes.
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Forecast accuracy stuck at 60–70%
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Safety stock over-built to compensate
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Stockouts on top sellers anyway
Three jobs, on rails.
SKU-level
Per-store / per-DC weekly forecast with confidence.
Promo + weather
External signals folded into the model.
Replenishment
Output drives PO suggestions in your ERP.
The path.
Connect three years of SKU × location × week sales history.
Layer promo calendar, weather signals, regional macro indicators.
Run the first quarter parallel to your current planning — measure the delta.
Switch the replenishment trigger to model output for the top 80% of revenue SKUs first.
One scenario, one outcome.
A grocery chain with 280 stores and 18,000 SKUs runs week-3 of summer.
Model predicts a 31% lift on chilled drinks Thursday onwards (heatwave + footy final). Safety stock is shifted that morning; stockouts on top-10 SKUs fall from 4.2% to 0.6% on the weekend.
Scoped on a call.
8–12 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.
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.
Geo & Satellite Analytics
Satellite + map data for OOH planning, agri yield, insurance underwriting and real estate due diligence.