Every station on one order spine, with Iris suggesting the upsell at the moment of sale.
The till: counter, tables, drive-thru, kitchen, dispatch, delivery and feedback on one order spine, with Iris suggesting the upsell at the moment of sale.
Counter, tables, drive-thru, kitchen, dispatch, delivery and feedback read the same order.
The suggestion lands while the guest is still at the till — not in next month’s report.
Kiosk, app, web and aggregators on one menu: an item goes 86 and disappears everywhere.
Checkout, returns, tender, tax, loyalty, offline resilience — standard in every Fashion sector.
IrisMeet the agent →Iris is the AI that narrates every screen, flags what needs a human and acts on the rest once approved. It names the cause, costs the move and proposes the action.
Deterministic thresholds that fire on the shift the breach happens — no model lag, no waiting for a report.
Forecasting and ML models that predict early enough to act on, with the cause named and the move costed.
Conversational layer: you ask what moved and why, and Iris answers with the recommended action for a human to approve.
Pick a sector to see the AI solutions in its catalogue that run on Point of Sale — named exactly as they appear in the playbook.
No Apparel & RTW solution is named for Point of Sale on its own — it runs underneath the board and reads the same data every other product writes.
No Footwear solution is named for Point of Sale on its own — it runs underneath the board and reads the same data every other product writes.
No Cosmetics & Beauty solution is named for Point of Sale on its own — it runs underneath the board and reads the same data every other product writes.
No Fabric & Textile solution is named for Point of Sale on its own — it runs underneath the board and reads the same data every other product writes.
No Home Textiles solution is named for Point of Sale on its own — it runs underneath the board and reads the same data every other product writes.
Modelled outcomes from the sector playbooks Point of Sale feeds.
Modelled from pilot assumptions and comparable F&B benchmarks — not yet a deployed-client result. Zentallio will publish real numbers as founding pilots conclude.
The executive board: Financial, Customer, Operational and AI-Learning lenses, each with its L1 rule thresholds, L2 model accuracies and an Ask Iris explanation of what moved and what to do.
Finance: executive cockpit, financial reporting and approvals in one ledger.
Supply chain: demand forecast, procurement and logistics tied to what actually sold.
Operations: standards, assets and energy across every site.
Workforce: rostering from forecast; overtime, absence and compliance handled before payroll.
Configured demo in 3–5 working days · no hardware · no long-term contract.