We build AI forecasting and automation systems for family-owned fuel and convenience retailers — so you order exactly what you'll sell, catch vendor billing errors, and finally have real visibility into which categories are making money.
Without sales velocity data by SKU, ordering becomes a guess. You over-buy slow movers and run out of fast sellers — losing both to waste and to missed sales.
Products approaching expiry get marked down or discarded. This isn't just the cost of goods — it's the labor that received, stocked, and managed inventory that never sold at full price.
Vendor invoices don't always match what was delivered — short quantities, wrong pricing, duplicate charges. Without systematic reconciliation, these errors cost you money every week.
You know total sales, but do you know which category — beverages, snacks, tobacco, foodservice — is actually profitable after shrink, labor, and vendor costs? Most operators don't.
AI analyzes your POS history, weather data, day-of-week patterns, and local events to predict demand by individual SKU. You know what you'll sell before you order it.
When inventory hits a reorder point, purchase orders are generated automatically and sent to your vendors — based on forecasted demand, lead times, and minimum order quantities.
AI matches vendor invoices against delivery records and POS data automatically — flagging quantity discrepancies, pricing errors, and duplicate charges before you pay them.
A daily dashboard showing gross margin by category, actual vs. expected shrink, and velocity trends — updated automatically from your POS data. No manual spreadsheet work.
Automated alerts when perishable products are approaching expiry — with suggested markdown timing to maximize recovery before product has to be discarded.
Track fill rates, delivery accuracy, and pricing compliance across all vendors — so you have data for vendor negotiations and can quickly identify which suppliers are costing you money.
Note: A personal note on this one — the founder of TreeHouse AI ran operations at a family-owned fuel and convenience store. This is the industry we know from the inside.
A single-location fuel station and convenience store losing thousands monthly to expired snacks and beverages, inconsistent ordering, and vendor invoices that frequently had quantity or pricing discrepancies that went uncaught.
Here’s what we’d build: AI demand forecasting connected to the POS, automated purchase-order generation, and an invoice reconciliation workflow that catches vendor discrepancies before they’re paid.
See Our Real Work →