AI Demand Forecasting & Auto-Replenishment for Odoo

This is a build-to-order module, not an instant download. After purchase we scope your sales history, catalog and warehouses, then engineer, install and validate the module — typically 2–4 weeks depending on data volume and how many warehouses and edge cases are involved. We deploy to staging first, run it against your real history, then promote to production with a rollback plan. You'll get a delivery timeline confirmed in writing at kickoff.

Every build includes a post-go-live support window for bug fixes and forecast tuning, plus documentation and a recorded training session. Beyond that window we offer ongoing support and maintenance plans, and we handle updates and Odoo version upgrades (17 → 18 → 19) as a defined, quoted service. Because we build the module for you, we know the codebase and can extend or adjust it as your catalog and processes evolve.

We build for Odoo 17, 18 and 19, on both Community and Enterprise. The forecasting layer and dynamic policy engine are custom Python, so they don't depend on Enterprise-only apps — but if you run Enterprise we integrate cleanly with its inventory and purchase features. Tell us your exact version and edition at kickoff and we target it precisely.

No — it enhances them. Instead of bypassing Odoo, the module writes its computed min/max, safety stock and reorder quantities back into the standard `stock.warehouse.orderpoint` records. Your Replenishment dashboard, procurement run and existing routes keep working exactly as your team knows them; the numbers are just smarter. You can also run it in advisory-only mode where it never writes back automatically.

Accuracy depends on your data history and demand stability, so we don't quote fictional numbers — instead the module tracks forecast accuracy (MAPE and bias) per product so you can see and audit real performance over time, and we tune the models during the support window. Purchasing stays human-in-the-loop by default: the system generates draft POs and transfers for your buyer to review and confirm. Full automation is available only if you explicitly enable it.

Forecasts are computed per `stock.warehouse`, so each location gets its own demand curve, safety stock and reorder policy rather than a blended company-wide figure. Access is controlled with `ir.model.access.csv` and record rules, so a planner can be restricted to only the warehouses they own. External systems can read forecasts and post actuals through documented JSON-RPC/XML-RPC endpoints, keeping your data inside Odoo.

Primarily your Odoo sales and stock history — `sale.order.line` and `stock.move` records — plus vendor lead times, MOQs, and holding/order cost assumptions. The more clean history you have, the faster the models warm up. We handle the backfill and ingestion as part of the build, and we validate the forecasts against known periods before go-live so you can trust the output.