Stockouts on best-sellers lose sales you never see
Product · Retail
IRIS
Intelligent Retail Inventory System
AI-powered stock replenishment and demand forecasting for multi-store retailers and distributors — one source of truth across every location.
1 to 1000+ stores from a single console
Solutions
The challenge
The problem IRIS solves
Retail teams still order by gut and spreadsheet — and it doesn't scale.
Overstock buries working capital in slow movers
Manual ordering breaks down past a handful of stores
Overview
What IRIS does
IRIS replaces manual ordering with intelligent recommendations and gives operators a single source of truth across every location.
Automated, intelligent replenishment recommendations
ML long-term demand forecasting (Prophet + custom models)
Conversational AI interface for natural-language inventory commands
Multi-store management (1–1000+ locations) with centralized control
Real-time KPI dashboards, alerts & performance metrics
Integrations with ERP, POS, and TMS
Inside the product
One platform, from the morning dashboard to the order in your ERP
Real screens from IRIS, connected to a 20-store cosmetics network.
01
Start the day with what needs a decision
The operations dashboard groups forecasts, orders, inventory and sales into three levels: immediate action, watch out, under control. Each line opens the SKUs behind it.
Anomalies ranked by business impact, not by alphabetical order
Filters by brand, category, city and store
Missing forecasts, stuck orders and active stock-outs in one view
02
Forecasts that know your calendar
Seasonal profiles are learned per category and per store, with Ramadan and Eid aligned on the lunar calendar. Fragrance, skincare and make-up do not peak on the same week, and IRIS does not pretend they do.
Profiles per category: fragrance, skincare, make-up, general retail
Year-on-year comparison and manual override with a reason
Launch ramp for new references without history
03
Validate, then let the ERP do the typing
Order proposals arrive per store and per supplier with the quantity, the value and the reason. Approve, adjust or reject; approved orders are created in Sage, Odoo, Dynamics 365 or SAP with the IRIS reference.
Approval thresholds by category and by value
Case packs, minimums and supplier calendars already applied
Status returned from the ERP: created, prepared, shipped, received
04
See stock health before the write-off
Stock by lifecycle, by ABC class and by store, with critical and warning counts. Slow movers, expiring lots and overstock are visible weeks before they become a loss.
Red, amber and green per SKU and store
Stock value and coverage in days
Transfer proposals to the store that will sell in time
How it works
How IRIS works
- Step 1
Connect
IRIS ingests sales, stock, and catalog from your POS/ERP.
- Step 2
Forecast
ML models (Prophet + custom) predict demand per store and SKU.
- Step 3
Recommend
IRIS proposes replenishment orders you approve in one click, or automate.
- Step 4
Learn
Every sell-through outcome sharpens the next forecast.
Outcomes
Outcomes teams see
~40%
fewer stockouts on top SKUs
~25%
less excess inventory
Hours/week reclaimed per store
Illustrative outcomes.
Use cases
Where IRIS fits
New-store ramp-up
Forecast demand before history exists.
Seasonal peaks
Plan promotions and buffer stock.
Slow-mover clearance
Time markdowns before cash is trapped.
Under the hood
- Prophet
- OpenAI
- FastAPI
- React
- PostgreSQL
- Redis
FAQ
Frequently asked questions about IRIS
Common platforms via API; we adapt to your stack.
From 1 to 1000+ from a single console.
No — start with recommendations you approve, automate when you trust it.
Typically weeks once your data is connected.
See IRIS on your data. In 30 minutes.
Live demo with a sample of your own store and inventory data — no slideware. We'll show you exactly what IRIS does for your team.