Reduce carrying costs and stockouts with predictive inventory
AI forecasts demand, optimizes replenishment and automates procurement.
Who it’s for
Retailers, wholesalers and manufacturers needing better demand forecasting and fewer out‑of‑stocks.
What it looks like in the field
- Carrying costs drop; demand forecasts improve; stockouts prevented with better planning.
Capabilities
- ML demand forecasting (sales, seasonality, external factors)
- Replenishment and PO recommendations
- Safety‑stock optimization and what‑if scenarios
- Supplier scoring and dynamic reorder points
How it works
- Import historical sales and stock data
- Forecast demand by SKU/location
- Optimize reorder points and safety stock
- Automate procurement and adapt in real time
Common integrations
ERP (SAP/Oracle/NetSuite), POS, e‑commerce, WMS, supplier portals.
KPIs
Carrying cost, stockout rate, fill rate, inventory turnover, forecast accuracy.
Security & compliance
On‑prem or private cloud; aligns with data‑governance frameworks.
Rollout (4–8 weeks)
Ingest data; configure models; pilot categories; scale across SKUs and locations.
Recommended Utlyze tier & pricing
Workflow Operator
Setup: — —/month
Most retailers
Autonomy Suite
Setup: — —/month
Large, multi‑brand supply chains
FAQs
How often are forecasts updated?
Daily or weekly cadence; real‑time adjustments as data arrives.
Can we include external factors?
Yes—weather, promotions and other datasets can improve accuracy.
On‑prem/private cloud deployment. Results vary by data quality and volatility.