CUSTOMER SUPPORT

Detect stalled tickets approaching SLA and escalate by age tier

Queries a Postgres support table for tickets with no agent activity, sorts them into aging tiers relative to their SLA deadline, and escalates each tier differently — Slack nudge.

CategoryCustomer Support
Enginesim
Difficultyintermediate
Triggerschedule
Steps5
Setup~15 min

How it runs

The automated pipeline, trigger to output.

  • TriggerEvery 15 minutes (schedule)
  • ActionQuery stalled tickets from PostgresPostgreSQLPostgres
  • LogicBucket tickets into SLA aging tiers
  • ActionTier 1/2: Slack nudge or manager pingSlack
  • OutputTier 3: page PagerDuty before breachPagerDutyPagerDuty

What it does

This workflow watches for tickets that have gone quiet. It pulls tickets from your Postgres helpdesk mirror, measures how long since the last agent touch against the SLA deadline, and applies graduated escalation: a gentle Slack nudge when aging starts, a manager DM as it worsens, and a PagerDuty page when a breach is imminent.

When to use it

Use it when tickets slip not because of volume but because they stall mid-thread. Graduated escalation avoids paging on-call for something a nudge would fix, while still guaranteeing a page before an actual breach.

How it works

  1. 1A schedule trigger runs every 15 minutes.
  2. 2Postgres returns open tickets with last-activity timestamps and SLA deadlines.
  3. 3A logic step buckets each stalled ticket into an aging tier based on percent of SLA window consumed.
  4. 4Tier 1 sends a Slack nudge to the assignee.
  5. 5Tier 2 escalates with a direct manager mention in Slack.
  6. 6Tier 3 pages PagerDuty for tickets within minutes of breach.

Set it up

What you configure once, before turning it on.

  1. 1
    Connect PostgresAny Postgres URL — query, write, migrate.
  2. 2
    Connect SlackChannels, DMs, threads, mentions.
  3. 3
    Connect PagerDutyIncidents, on-call, escalations.
  4. 4
    Set each agent's modelWe leave models unset so you pick the tier — fast + cheap, or top-quality.
  5. 5
    Tune it to your dataEdit the prompts, filters, and field mappings so it matches how your team works.
  6. 6
    Test, then turn it onRun once against a sample, confirm the output, then enable the trigger.

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