AI x Supply Chain: Forecast replenish and reconcile without spreadsheets
Supply chain agents for demand forecasting, replenishment, exceptions, and reconciliation.
Workflow Engine
Lead→Deal→Quote→Order→Invoice→Payment→Reconciliation→Renewal
Synced
All systems
Active
12 workflows
Audit trail
100% logged
One workflow engine. One audit trail. One source of truth.
Trusted by 1,000+ fast-moving sales teams
AI x Supply Chain: forecast, replenish, and reconcile without spreadsheets
Supply chain AI is only useful if it acts on real item master, inventory, and purchase data. Sanka supply chain agents sit on top of your items, locations, and PO history — so they can suggest reorder points, flag exceptions, and draft POs that your buyers can approve in one click.
Demand & replenishment
Forecast by SKU and location using sales history, lead times, and safety stock, then draft replenishment POs for review.
Exception handling
Surface stockouts, overstock, and slow movers with explainable reasons — not just dashboards to interpret.
Reconciliation
Match POs to receipts and invoices, reconcile inventory transactions, and keep a clean audit trail for finance.
Scope the first supply chain agent
- Start with a single category or warehouse instead of the whole item master.
- Fix master data: BOM, unit of measure, lead time, and supplier mapping must be trustworthy before AI acts on them.
- Require human approval on purchase orders above a threshold, and log every suggestion with its input data.
| Layer | Decide up front | Example |
|---|---|---|
| Data | Which items and locations are in scope | Top 200 SKUs in one region |
| Signals | What the agent reads | Sales velocity, lead time, safety stock |
| Action | What the agent may draft | Replenishment PO, transfer order, alert |
Outcomes operations teams expect
- Fewer stockouts and less dead stock, with traceable forecasts.
- PO drafts instead of blank spreadsheets, with buyer approval in the loop.
- Finance can reconcile receipts and invoices without chasing operations.