AI that finds the stockout
before your customer does.
Upload store inventory, POS data or sales reports. OpsOracle AI flags active stockouts, identifies dead inventory tying up working capital, scores sell-through by SKU, and tells your buying team exactly what to act on — in under 30 seconds.
Retail AI Capabilities
Built for buyers, merchandisers and store managers
Not a generic AI. Every engine is calibrated on retail signals — sell-through velocity, stockout cost, dead inventory carrying cost, returns root causes.
Stockout Detection & Alerting
Scan every SKU across every store for zero or near-zero stock against real demand velocity. AI flags stockouts before customers hit an empty shelf — with revenue loss quantified per day.
Dead Inventory Identification
Find SKUs where stock weeks-on-hand far exceeds sell-through velocity. AI calculates working capital locked in slow movers and recommends markdown timing before the seasonal window closes.
Demand Forecast Accuracy
Compare actual weekly sales against forecast per SKU. AI names the specific products where buys were over or under by the most — so your merchandising team can fix the forecast model before next season.
Returns Rate Analysis
Detect SKUs with abnormal return rates and correlate with sales velocity, sizing data or product category. AI identifies whether high returns signal a product defect, sizing issue or misleading listing.
Sell-Through Scoring
Score every category and SKU on sell-through percentage against plan. AI ranks your worst-performing categories so the buying team knows where to cut inventory investment in the next buy cycle.
Cross-Store Inventory Rebalancing
Identify where the same SKU is overstocked in one store and understocked in another. AI recommends inter-store transfers to maximise sell-through without fresh procurement.
Real Pain → AI Solves It
Your team faces these every week.
OpsOracle names them and fixes them.
Actual AI output from real Retail data. Upload your report and get this analysis in under 30 seconds.
The Pain
3 of our best-selling SKUs are out of stock. We found out when customers started complaining. We're losing ₹40,000 a day.
Raw data signal
SKU-202 stock=0 · weekly demand 28 · last restock 2026-05-20 (21d ago) | SKU-206 stock=0 · demand 15/wk | SKU-210 stock=0 · demand 19/wk
OpsOracle AI Output
SKU-202 (Samsung Charger), SKU-206 (Yoga Mat), and SKU-210 (Bluetooth Speaker) are all at zero stock across Mumbai and Delhi stores. Combined weekly demand: 62 units. At current sell price, that is ₹46,200 in weekly revenue stopped. SKU-202 has been stockout for 21 days.
[THIS WEEK] Action
Buying team to raise emergency POs for all 3 SKUs today — accept 15% express procurement premium. Prioritise SKU-202 (highest demand, longest stockout). Set auto-reorder triggers at 30-unit threshold across all three.
Expected impact: Recover ₹46,200 weekly revenue; prevent further customer churn to competitor for fast-moving electronics
The Pain
Winter jackets are taking up shelf space. 220 units, barely selling. Meanwhile summer products are out of stock.
Raw data signal
SKU-208 Winter Jacket L: stock=220 · weekly_sales=2 · sell_through=67% · returns=31 · days_until_stockout=110
OpsOracle AI Output
SKU-208 has 220 units selling at 2/week — 110 weeks of stock at current velocity. 31 returns suggest sizing or quality issue compounding the problem. Carrying cost: ₹1,76,000 in locked working capital. Seasonal window for winter apparel has closed.
[THIS WEEK] Action
Merchandising team to markdown SKU-208 by 30% this week — target sell-through of 80 units in 3 weeks before monsoon season. Simultaneously review reorder settings: this SKU should not have been restocked at current levels.
Expected impact: Free ₹1,76,000 in working capital; open shelf space for monsoon/summer high-velocity SKUs
The Pain
Summer Dress SKU is sitting at 145 units but barely selling. Forecast said 25/week. Actual is 8. Nobody adjusted the buy.
Raw data signal
SKU-203 Summer Dress Red: stock=145 · weekly_sales=8 · forecast=25 · sell_through=32% · returns=18
OpsOracle AI Output
SKU-203 actual demand is 32% of forecast (8 vs 25 units/week). With 145 units in stock, you have 18 weeks of supply at real velocity — far beyond season. 18 returns (12% return rate vs 3% category average) suggest a product-fit issue driving both low sales and high returns.
[THIS WEEK] Action
Category manager to review SKU-203 customer return reasons this week — if sizing: raise exchange policy. Reduce buy plan for this SKU next season by 65%. Consider bundling with fast-moving accessories to increase basket conversion.
Expected impact: Prevent end-of-season markdowns; save ₹87,000 in potential inventory write-down next quarter
14-day Pro trial · No credit card · Results in 30 seconds
How retail teams use OpsOracle AI
Upload your inventory or POS export
Export your store inventory, weekly sales report or POS data as CSV. OpsOracle reads any column format — no template required.
AI scores every SKU's health
Stockouts flagged with daily revenue loss, dead inventory ranked by working capital locked, demand forecast misses identified by SKU. All in one analysis.
Act before the week is over
Three specific actions — emergency PO, markdown trigger, inter-store transfer — each names the SKU, the store, and the rupee impact of fixing it today.
Stop losing sales to stockouts you could have predicted.
Upload your inventory report now — OpsOracle AI returns stockout alerts, dead inventory analysis and demand forecast scores in seconds.
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