POS AI Upsell & Recommendations

ECOSIRE builds a dedicated POS module that adds a real-time recommendation engine on top of your existing catalog. On the backend we add Odoo models (models.Model) that store recommendation rules, affinity pairs, and per-daypart configuration, with @api.depends computed scores and a service layer that reads historical pos.order / pos.order.line data to derive frequently-bought-together associations (a market-basket / co-occurrence pass you can re-run as a scheduled ir.cron automated action). The POS front end is extended through OWL components and patches to the point-of-sale JavaScript so that, as products are added to the current order, the screen surfaces contextual add-on and combo cues to the cashier — and the same engine drives suggestive prompts on the self-order kiosk screen. Suggestions can be weighted by time of day, and optionally by a weather signal pulled through a guarded outbound call, so cold-drink or hot-item prompts shift with conditions. Everything respects Odoo access control: recommendation configuration is governed by ir.model.access.csv plus record rules so store managers edit rules while cashiers only consume them, and all analytics honor multi-company boundaries.

Because it is native Odoo, the module ships as a proper addon with its own __manifest__.py declaring dependencies on point_of_sale (and pos_restaurant where combos apply), migration-safe schema, XML/OWL views for the configuration screens, and a QWeb "upsell performance" report so you can see attach-rate and incremental revenue per suggestion. Recommendation data is exposed over the standard XML-RPC / JSON-RPC API so external analytics or a headless kiosk can read the same suggestions the POS uses. We target Community and Enterprise on Odoo 17.0, 18.0, and 19.0 — the recommendation logic and OWL components are written against your exact version so nothing depends on undocumented internals, and we flag any Enterprise-only touchpoints (such as advanced kiosk/self-order screens) up front during scoping.

This is a build-to-order engagement, not an instant apps.odoo.com download. After a short scoping call we confirm your Odoo version, edition, POS/kiosk topology, and which upsell behaviors matter most, then produce a fixed scope. Typical delivery is 2–4 weeks from confirmed scope. We develop against a staging copy of your database, run UAT with your team, and only then install on production with a documented rollback path. You receive the full source, the git repository, technical and user documentation, a training session, and a post-go-live support window — so the engine keeps performing as your menu and traffic patterns change.