The operating problem
A merchandising team investigates stock discrepancies and inconsistent product information across stores and digital channels. The workflow is not simply a question-answering task: it requires a reliable relationship between business entities, current evidence, and the review responsibilities of staff.
The same product may have inconsistent catalog attributes across channels, while stock positions change faster than scheduled reports. A useful initial scope therefore focuses on assembling the right context and making missing information visible. It avoids treating a generated answer as an approved business decision.
The proposed data foundation
Potential inputs include product catalog, stock positions, demand history, service tickets. Establish a source inventory before choosing connectors. For each input, record its owner, approved use, identifier conventions, update cadence, and retention requirements.
Define stable SKU and location keys, distinguish on-hand from available-to-promise stock, and retain event timestamps and units. The curated domain model centers on SKU, Location, Inventory event, Product attribute. Keep raw source evidence separate from validated records and from the outputs prepared for a reviewer. This separation makes reconciliation and incident investigation more manageable.
AI and agent responsibilities
Find stock discrepancies and draft replenishment recommendations. A permission-aware retrieval layer can assemble the relevant approved context. Extraction or generation should return structured drafts, source references, and unresolved questions; it should not silently supply facts that are absent from the records.
Suggest structured descriptions and flag inconsistent product attributes. A second bounded responsibility can handle a related task while retaining the same identity and governance boundary. Multi-agent coordination is optional: use it only when separated responsibilities improve traceability or control.
Human review and exception paths
Pricing, purchase orders, inventory adjustments, and published catalog changes require business approval. Missing documents, conflicting records, unavailable tools, and low-quality retrieval should lead to a visible exception. Define who can resolve each exception and what evidence must be retained with the decision.
How the scenario would be evaluated
Proposed evaluation areas: event freshness, stock reconciliation accuracy, catalog exception precision, and recommendation review effort. Build a representative set containing normal cases, incomplete cases, outdated information, access restrictions, and tool failures. Compare the assisted workflow with the current process using the same acceptance criteria.
No percentage improvement, cost saving, or production result is asserted here. Any future benefit estimate should follow a measured baseline and a reviewed pilot, including the effort required to correct outputs and handle exceptions.
A focused next step
Agree one workflow, one accountable owner, a limited source set, and a review protocol. Use the first prototype to identify data gaps and operational changes, then decide whether additional integrations are justified.