A wrong classification has to stand out
If a category or priority is assigned incorrectly, an urgent request must not sit silently in the background; a low-confidence result needs to be visible.
Incoming email was read and sorted by hand; urgent messages sometimes got lost in the pile. We built SmartMail Orchestration as a layer that reads every email with GPT, classifies it by category, priority and required action, then opens a task or notifies the right system through a webhook.
Requests landing in the inbox were read and sorted one by one; urgent ones got lost among the rest.
If a category or priority is assigned incorrectly, an urgent request must not sit silently in the background; a low-confidence result needs to be visible.
Spam filtering can't be so aggressive that it drops a genuine request.
Opening a task and triggering a webhook each need a different data shape depending on the connected system; the integration can't fit one single pattern.
Incoming email goes through GPT-based content parsing, which determines category, priority and content type. Based on the result, the relevant task opens or a webhook notifies the target system; spam is kept separate.
{ "email_id": "SM-2026-018204", "category": "support", "priority": "high", "action": "open_task", "confidence": 0.92}{ "email_id": "SM-2026-018204", "category": "support", "priority": "high", "action": "open_task" }