AI Inventory Prediction
Machine-learning demand forecasting built into Odoo replenishment: SKU-level forecasts per store, seasonality and promotion effects, and AI-suggested purchase orders that buyers approve in one click.
- Client
- RetailGiant Inc
- Category
- Retail
- Platform
- Odoo 17 Inventory + Python ML service
- Duration
- 12 weeks
- Team
- 5 specialists
0%
fewer stock-outs
0%
less excess inventory
0%
forecast accuracy (weekly)
RetailGiant's buyers set reorder points by gut feel. Popular items sold out during promotions while slow movers piled up in the back room, tying up cash and shelf space.
They wanted forecasts that learn from sales history, seasons and promotions, delivered inside the Odoo screens buyers already use.
AI demand forecasts with confidence bands and explainable suggestions. Try approving one.
Weekly demand · SKU group Grocery
AI forecastBasmati Rice 5kg
Store 04
Laundry Gel 3L
Store 11
Olive Oil 1L
Store 02
Illustrative view with representative data.
Noisy, incomplete sales history
Stock-outs hid true demand, and SKUs were renamed or merged over the years.
We cleaned and mapped SKU history, then corrected demand for stock-out days so the model learns what customers wanted, not just what was available.
Thousands of SKUs × stores
One model per SKU was too slow and unstable for the long tail of items.
A global gradient-boosting model with SKU, category, store, seasonality and promotion features forecasts every combination in minutes, with fallbacks for new items.
Getting buyers to trust AI
Buyers ignored suggestions they couldn't understand.
Each suggestion shows the forecast, safety stock and the drivers behind it (season, promo, trend), and buyers can override with a reason that feeds back into training.
- Data pipeline from Odoo sales, stock and promotions
- SKU × store demand forecasts with confidence intervals
- Dynamic safety stock and reorder points
- AI-suggested purchase orders inside Odoo
- Forecast accuracy and stock-health dashboards
- Weekly automatic model retraining
How the system flows
- 1Sales data synced
- 2Model retrained
- 3Forecasts generated
- 4Reorder points updated
- 5POs suggested
- 6Buyer approves
Key operating metrics before the project and after go-live.
Stock-out rate
-32%Days of inventory on hand
-22%Buyer time on replenishment
-70%
API IntegrationsSaksooka
J&T Delivery Service Integration
Native integration between Odoo and J&T Express: shipments booked from delivery orders, labels printed in one click, live tracking pushed back to Odoo and cash-on-delivery reconciled automatically.
0%
less manual booking
0%
fewer failed deliveries
<0 day
COD reconciliation
Point Of SaleMultiple clients
Commission on POS
A configurable sales-commission engine for Odoo Point of Sale, deployed for multiple retail clients, that calculates commissions per cashier and salesperson in real time and pays them through payroll.
0%
automated commission calculation
0
month-end disputes
0%
uplift in attach sales
API IntegrationsTonerOne
eBay API Integration
Two-way integration between Odoo and eBay for a printer-consumables seller: listings, prices and stock published from Odoo, orders imported automatically and tracking numbers pushed back to buyers.
0
oversold orders since go-live
0%
less manual order entry
<0 min
stock sync latency
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