Walk the Support Routing Decision
Apply supervised-learning and inference concepts to a customer-support routing use case.
Live queue New tickets must be routed in under five seconds, but many historical annotations were added after agents already investigated the case. The best-looking training fields may not exist when inference has to happen. Question -> label -> serve Route from decision point, not from dataset nostalgia Start with the business decision, confirm the label, then check whether the live workflow has the same information at inference time. Use every historical field Feels rich, often breaks at serve time. The model only moves forward if training logic matches the inference moment. A production use case survives only when label…
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