Run a head-to-head on a labeled sample (≥200 tickets): same prompt, low temperature, few-shot examples. Measure tag precision/recall, summary ROUGE/qualitative accuracy, hallucination rate, latency and cost. For long threads chunk context and include ticket metadata. Use Zapier to trigger model calls and write suggested tags as draft for human verification; keep a human-in-the-loop feedback loop to retrain prompts or classifiers. Start with ChatGPT as a baseline and compare against Claude for instruction-following.

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