Artiplane · enterprise AI platform

Inventory rebalancing, from signal to measured result

The canonical use case: a coverage gap in Italy, excess in Germany, an STO approved within authority.

Use case

2026-09-10 · 7 min read

Key takeaways

  • The signal comes from the semantic layer, not from a report.
  • Simulation shows the projected impact before approval.
  • The result is measured seven days later and remembered.
How an enterprise RAG answer is built

ERP, PLM, CRM and documents keep provenance and version.

The signal

The Stock Agent reads coverage per market on the canonical Product and flags Italy at 17.6 days against a healthy Germany.

Evidence arrives with its sources: SAP inventory, POS sell-out, commerce demand.

The decision

The Buyer Orchestrator proposes a transfer and simulates it: stock after the move, projected markdown avoided, alternatives.

Above the buyer's limit the decision routes to the merchandising director; nothing executes before approval.

The measure

The approved action becomes a registered STO with its reference, and seven days later the platform reports the measured effect.

That measurement is what turns one decision into a rule the organisation can reuse.

FAQ

Frequently asked questions

Why does “The signal” matter?

The Stock Agent reads coverage per market on the canonical Product and flags Italy at 17.6 days against a healthy Germany. Evidence arrives with its sources: SAP inventory, POS sell-out, commerce demand.

How does “The decision” work?

The Buyer Orchestrator proposes a transfer and simulates it: stock after the move, projected markdown avoided, alternatives. Above the buyer's limit the decision routes to the merchandising director; nothing executes before approval.

What should a team know about “The measure”?

The approved action becomes a registered STO with its reference, and seven days later the platform reports the measured effect. That measurement is what turns one decision into a rule the organisation can reuse.

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