Every busy retail floor hits the same wall: the data you need to react is trapped in reports you run after the shift is over. Odoo's native Point of Sale is excellent at capturing transactions, but its out-of-the-box reporting leans on the standard pos.order pivot and graph views, which are query-on-demand snapshots — you refresh a report and see where things stood a moment ago. There is no native push channel that keeps a wall-mounted screen or a manager's tab live as orders close, no built-in "you are about to run out of your top seller" signal on the floor, and no consolidated multi-register, multi-store view that updates without someone clicking. When a promotion spikes demand or a fast-moving SKU quietly drains to zero, you find out from the report, not in time to act on it.

POS Live Dashboard is a custom Odoo module ECOSIRE builds for exactly that gap. It ships as a proper addon (__manifest__.py declaring dependencies on point_of_sale, stock, and sale) with dedicated dashboard models (models.Model) whose figures are computed fields driven by @api.depends on pos.order and pos.order.line, so revenue, units, average basket, gross margin, and per-cashier throughput stay derived from your real transactional data rather than a duplicated cache. The front end is an OWL component rendering into a QWeb template, subscribed over Odoo's bus (bus.bus / longpolling, or websocket on 17/18/19) so open sessions receive push updates the instant an order is validated at any register — no manual refresh, no polling loop hammering the database. Charts are rendered client-side (Chart.js-style canvas inside the OWL widget) for sales-over-time, category mix, hourly heat, and top-product leaderboards.

The inventory-suggestion engine is where it earns its place on the floor. A server-side compute reads current stock.quant on-hand against a rolling sell-through rate calculated from recent POS lines, projects hours-to-stockout per product for the active session, and surfaces a ranked replenishment list — configurable thresholds live in a settings model so each store tunes its own reorder sensitivity. Optionally, an ir.cron scheduled action or an base.automation automated action can fire an Odoo activity or internal note to the stock team when a flagged product crosses its threshold, so the suggestion becomes an assignable task, not just a number on a screen. Everything is permissioned properly: access rights via ir.model.access.csv plus record rules scope each dashboard to the salesperson's own pos.config/store on multi-store estates, and manager roles see the consolidated roll-up. Where you want it embedded elsewhere, the same KPI models are readable over the standard XML-RPC/JSON-RPC API. The module targets Odoo 17.0, 18.0, and 19.0 and works on Community (bus-based live updates) as well as Enterprise, with the build noting any Enterprise-only niceties your edition unlocks.

Because this is build-to-order, you are not downloading a fixed app and hoping it fits — we scope it to your registers, your product taxonomy, and your reorder logic first. After a short scoping call we confirm the KPI set, the stockout model, store-level access rules, and target Odoo version, then build against a staging copy of your database, run UAT with your team, and deploy with a rollback plan. Typical delivery is 2 to 4 weeks from confirmed scope. Pricing starts from $249 (indicative, single-company base scope); multi-company or multi-warehouse roll-ups, deeper localization, additional integrations (e-commerce, external BI, or hardware displays), and migration of historical POS data to backfill trend charts increase the quoted scope. You receive the installable source, documentation, training, and a post-go-live support window — the final fixed quote is agreed after the scoping call.