Supply-chain managers live inside Odoo's Inventory, Purchase and Sales apps, but the questions that actually matter — "which SKUs will stock out before my next PO lands?", "who is my most reliable vendor for this category by lead time, not just price?", "what should I pre-buy for the Q4 season?" — take a spreadsheet export, a pivot table, and an hour of manual work each time. Native Odoo gives you reordering rules (stock.warehouse.orderpoint), forecasted quantities, and the Replenishment view, but they answer fixed questions in a fixed layout. There is no way to simply type a question and have the system reason over your live stock moves, sale order history and purchase lead times to give you a ranked, explainable answer. That gap is where teams fall back to gut feel and stale exports.

We build a Natural-Language Inventory & Supply Assistant as a proper Odoo module tailored to your database. At its core is a new model (for example nl.supply.query) plus a chat-style OWL widget embedded in the Inventory app. A user types a plain-English question; the module maps it to a safe, parameterized set of intents — replenishment, vendor ranking, seasonal demand, stock-position lookup — and runs vetted ORM queries against stock.move, stock.quant, sale.order.line, purchase.order.line and product.supplierinfo. Answers come back as structured cards and tables, not free-text guesses: a replenishment suggestion shows the SKU, forecasted demand, current on-hand and incoming, the recommended quantity, and the reasoning behind it. Vendor ranking is computed from real receipts — lead-time variance from purchase.order confirmation-to-receipt deltas, fill rate, and unit price — surfaced through @api.depends computed fields so the numbers stay live. Where an LLM is used to parse intent, it never writes SQL or touches records directly; it only classifies the request into your approved query catalog, honoring the "never sql.raw()" rule.

Technically, the module ships as a self-contained addon: __manifest__.py declaring dependencies on stock, purchase and sale; models under models/ using models.Model with computed forecast and vendor-score fields; access control via ir.model.access.csv and record rules so managers only see their own warehouses and companies; XML/OWL views for the assistant panel and a forecast + supply dashboard; and QWeb report templates so any answer — a replenishment plan or a vendor scorecard — can be exported to PDF for a purchasing meeting. Optional ir.cron automated actions can push a daily "what needs ordering" digest, and everything is reachable over Odoo's XML-RPC/JSON-RPC API if you want to query it from another system. We build for your edition: Community and Enterprise differ (Enterprise adds the native forecast report and studio-style tooling), so we scope forecasting depth to what your license and data support rather than assuming Enterprise-only features.

Because this is build-to-order, nothing is downloaded and switched on blind. We start with a short scoping call to confirm your Odoo version (17.0, 18.0 or 19.0), edition, warehouse structure and the specific questions you need answered. We then build against a copy of your data on staging, run UAT with your team, and only deploy to production once you sign off — typically 2 to 4 weeks from confirmed scope, depending on how many query intents and dashboards you need. You receive the full installable source, technical and user documentation, a training session, and a post-go-live support window. If it needs to change later, you own the git repo and we support it.