Predict SLA breaches from ticket history and open ClickUp tasks

This workflow learns from your past tickets. It reads resolved-ticket timing from a Postgres analytics table to build a per-category expected-resolution baseline, scores each currently open ticket against that baseline plus its remaining SLA budget, and opens a ClickUp triage task for any ticket whose risk score is high. The score, deadline, and reason ride along on the task.

Use it when raw timers aren't enough and you want data-driven risk — tickets in slow categories or with stalled activity flagged earlier than a naive countdown would. Good for teams that already warehouse ticket metrics in Postgres.

1. 1A schedule fires hourly.
2. 2It queries Postgres for resolved-ticket timings to compute expected resolution by category.
3. 3It loads currently open tickets and their elapsed time and activity.
4. 4A scoring step combines category baseline, remaining SLA budget, and recent activity into a breach-risk score.
5. 5A branch keeps tickets above the high-risk threshold without an existing triage task.
6. 6It creates a prioritized ClickUp task per high-risk ticket and records the score back in Postgres.