Warranty waiver review

The scenario and numbers in this demonstration project are simulated data.

Industry: Consumer electronics distribution and service
What was built: Agents, skills, semantic models and write tools, built on demonstration data
Where the knowledge came from: The manufacturer's service bulletin, plus demonstration data from the CRM, repair work order, ERP spare parts and warranty claim systems

Refusal terms and bulletins

A business customer sends in a laptop for repair. Its liquid contact indicator has changed colour, and the manufacturer's warranty terms allow refusal when it does.
The store technician searches the service bulletin database and finds a bulletin from the manufacturer: a heat event on this batch of mainboards can trip the indicator by mistake.

The manufacturer's service bulletin sits in Drive. The agent reads it and compares the model, serial batch and symptoms, and confirms that all of them meet the bulletin's conditions.
The bulletin says a mistakenly tripped indicator qualifies for a warranty waiver, with a diagnostic log and serial confirmation attached.
The bulletin also says not to judge the cause of failure from the indicator alone.
The agent checks the warranty policy through semantic models: a warranty waiver needs the customer service manager's approval, and a manufacturer claim needs the bulletin number and diagnostic screenshots.
The agent checks the purchase date and warranty term in the CRM through semantic models, and confirms that the laptop is still under warranty.
The agent checks the repair work order history, confirms there are no repeat repairs for the serial, and rules out user damage.

Only one matching mainboard is left. The agent ranks the work orders for the last part by remaining SLA time and available workarounds. The agent also prepares a draft manufacturer claim.
The warranty waiver, the last part's allocation, the rush purchase order and the claim submission all wait for the customer service manager's approval before the agent writes them back.

At companies like this, manufacturer service bulletins and repair records will keep coming in.
The agent will collect feedback on its answers from users. The feedback will go to Odin.
Wrong answers will become tests. A change will be kept only if scores improve.

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