Handle peak order enquiries through exception queues

Start with the operational bottleneck

Seasonal peaks expose the difference between repetitive work and complex support. Many enquiries ask where an order is, how a policy applies, or whether a request was received. Others involve missing parcels, conflicting records, or a disappointed customer needing a judgement call.

Map those paths before introducing an assistant. Identify which enquiries can be answered from verified order data and approved policy, and which must reach a person. A customer asking repeatedly is a signal of unresolved work, not several independent successful conversations.

Design the target workflow

Verify the customer using the existing support process before exposing order information. Retrieve the relevant order state and policy. Use rules for straightforward status mapping, and a model to draft a clear response from the approved facts.

Route exceptions into named queues with the order reference, evidence, attempted steps, and reason for escalation. Preserve customer edits and agent decisions. Start with read-only responses; keep refunds, address changes, and cancellations behind separate permissions and approval. An outage in the commerce platform should produce a useful fallback rather than a guessed answer.

Connect to the existing systems

Connection	Information	Control
Helpdesk	Verified identity and conversation history	Respect the existing customer verification flow
Order system	Status and fulfilment events	Read only the records needed for the request
Exception queues	Evidence and unresolved action	Name an owner and track repeat contacts

Use stable identifiers and versioned inputs. A retry should resume the same piece of work, with the original permissions and evidence attached. Treat an upstream outage as a visible workflow state.

Fit the model to the task

A small model is often a reasonable candidate for intent classification and bounded drafting. Evaluate multilingual, ambiguous, and emotionally charged enquiries. Routing rules and access controls belong outside the model; they should continue working when generation fails.

Keep a clear human boundary

Test requests to reveal another customer’s order, override a policy, or follow instructions embedded in uploaded text. A human reviews exceptions and authorised financial actions. Keep an audit trail of the data read and the response issued.

Measure the complete operating cost

Measure repeat contact, correction rates, handoff time, and total handling effort. Report coverage and resolution with clear denominators: a resolved share of touched conversations is different from a share of all incoming work. Include peak-period capacity and support staffing.

Pilot checklist

• Define routine, ambiguous, and consequential enquiry classes.
• Test identity and order-access boundaries.
• Provide a fallback when upstream systems fail.
• Track repeat contacts and human correction effort.
• Evaluate the entire support workflow through the demand peak.

Agree on acceptance thresholds before testing, then compare the proposed workflow with the same work handled through the current process. Expand only after the operation can explain both successful and failed cases.

Further implementation detail

• Choose the lowest-cost model that meets the task requirements
• Serve a local model to a team
• Ollama’s local API reference