Refund requests are emotionally charged, time-sensitive, and almost entirely repetitive. The same conversation, over and over: customer wants money back, agent asks for order number, agent looks up policy, agent explains why or why not, customer pushes back, agent gives a partial refund anyway. Each one eats 15 minutes and lowers morale on both sides. Generic chatbots cannot help because they cannot read the order or apply the policy, so they end every conversation with we will get back to you within 48 hours.

SleekAI handles refund requests by reading the order from wp_wc_orders, the item line and refund history from wp_wc_order_items, and your refund policy from a configured page or meta field. It checks the purchase date against your refund window, looks at whether the item has been delivered (via tracking meta), and reads any per-product no-refund flag. The bot then tells the customer the answer with a clear reason: yes, partial, or no, with the policy quote and order details attached.

The complex cases route correctly. Damage claims trigger a photo upload flow. Subscription refunds check the billing cycle. Gift refunds verify the original purchaser. Items past the window can still be offered store credit if your policy allows. The bot writes a structured ticket to wp_sleekai_conversations plus your help desk, so the human picking it up sees the full conversation, the order, and the policy decision the model already made. Approvals happen faster, denials are consistent.

Refund tickets are the single most expensive support interaction at most ecommerce stores, not because of the refund itself but because of the human time consumed. Most refund conversations follow a script. Customer states a reason, agent looks up the order, agent compares against the policy, agent explains the answer, customer accepts or pushes back.

The model can run this entire script in seconds given the right inputs. The catch is the inputs. The order, the items, the dates, the policy text, the per-product flags, the customer history, all live in WordPress.

A generic chatbot sees none of this. So it ends every conversation with a generic we will respond within 48 hours, which means the human still does all the work, just later and with an irritated customer. A policy-aware bot changes the economics.

Clear-cut approvals close in two minutes. Clear-cut denials cite the exact policy paragraph and offer the documented alternative, which the customer accepts far more often than a vague no from a human agent. Edge cases still escalate, but they escalate with a one-paragraph summary instead of a fresh ticket.

There is a fairness benefit too. Humans tire and bend policy inconsistently after a long shift. The bot applies the same rules to every customer, every time.

When a real exception is warranted, a human still has the final say. That combination, consistent triage plus human override, is exactly what most refund policies were meant to deliver in the first place.