Fresh Produce AI Forecasting
Fresh Produce Forecasting Software: Reduce Shrinkage & Eliminate Stockouts
Purpose-built demand sensing for perishables. Predicts demand at SKU level, improves on-shelf availability, and reduces grocery shrinkage by up to 76% — verified in a 30-day, 100-store pilot.
Why Standard ERP Modules Fail at Fresh Produce Forecasting
Fresh produce operates by different rules. Standard demand planning algorithms were not built for fresh categories — and the cost shows up in shrinkage rates and phantom inventory.
Shrinkage Compounds Daily
Standard ERPs treat every SKU as identical inventory. Without expiry-aware demand sensing, fresh categories accumulate ghost stock — product that shows in the system but is already unsellable on the shelf.
Day-of-Week Demand Is Non-Linear
Strawberry sales on Friday differ from Monday by 40–80%. Most systems use weekly averages, which systematically under-order for peak days and create over-order shrinkage on slow days.
Promotional Lift Goes Unmodeled
Promotions, local events, and weather create demand spikes that historical averages cannot predict. Without promotional lift modeling, you over-stock before and under-stock during every event.
How Our Fresh Produce Forecasting Works
Real-Time POS & WMS Integration
Direct integration with your existing systems — sales velocity and inventory levels update within the hour, eliminating the stale-data problem that drives phantom inventory.
SKU-Level Demand Curves with Expiry Awareness
Every SKU gets its own store-level forecasting model. Milk, strawberries, and bakery are forecast separately — each with expiry-adjusted order quantities.
Demand Sensing: Weather, Events, Promotional Lift
Weather forecasts, local events, school calendars, public holidays, and promotional calendars feed the model automatically — capturing every lift before it happens.
Automated Ordering & Closed-Loop Learning
Orders are generated and submitted to your ERP. Every cycle feeds the model — on-shelf availability improves continuously as the system learns your specific stores.
Results in Fresh Categories
76%
Write-Off Reduction
from 5.8% down to 1.4%
91.8%
Shelf Availability
up from 70% baseline
+24%
Sales Growth
in the 30-day pilot period
Results measured in a 30-day, 100-store pilot. Individual results may vary.
Start a 30-Day Pilot
No upfront cost. No commitment.