The agent uses LLM-driven analysis to assess how quickly and effectively issues are resolved based on historical ticket data and SLA benchmarks. It evaluates time to first response, overall resolution time, and response cadence, flagging tickets where delays could have been avoided. The agent also considers whether the pace of resolution aligns with the complexity of each issue, helping teams balance speed and quality.
In addition to timing, the agent reviews tone, professionalism, and factual accuracy. It highlights responses that, while correct, may lack empathy or clarity, and suggests alternative phrasing to enhance customer experience. This ongoing, AI-powered feedback enables support teams to refine communication, maintain consistent standards, and deliver faster, more thoughtful service at scale.
[image] => https://d3tfuasmf2hsy5.cloudfront.net/assets/worker-templates/compliance-risk-assessment-agent.svg [video] => [icon] => https://d3tfuasmf2hsy5.cloudfront.net/assets/worker-templates/compliance-risk-assessment-agent.svg [sourceType] => FILE [status] => REQUEST [department] => Customer Service [subDepartment] => Ticket QA [process] => Resolution Review [subtitle] => Evaluates closed support tickets for accuracy, tone, empathy, and resolution speed using LLMs to suggest quality improvements. [route] => resolution-quality-rating-agent [addedOn] => 1754655166330 [modifiedOn] => 1754655166330 ) )Evaluates closed support tickets for accuracy, tone, empathy, and resolution speed using LLMs to suggest quality improvements.