CUSTOMER SUPPORT
Front SLA risk ledger to Postgres with trend alerts
On a schedule, records every open Front conversation's predicted SLA risk into a Postgres ledger.
How it runs
The automated pipeline, trigger to output.
- TriggerEvery 15 minutes (schedule)
- ActionList open Front conversations with deadlinesFront
- LogicScore and tally breach-risk buckets
- ActionInsert snapshot into Postgres ledgerPostgres
- LogicCompare recent snapshots for rising trend
- OutputPost staffing alert to Slack if trending upSlack
What it does
Builds a time-series record of SLA pressure instead of just reacting to single threads. Each run snapshots all open conversations, scores each one's breach risk, and writes the rollup into a Postgres table. It then compares the latest snapshot against the prior few to detect a rising backlog and warns the team while there's still time to add coverage.
When to use it
Use it when individual reassignments aren't enough and you need to see whether the inbox is structurally falling behind — a surge, an understaffed shift, or a creeping backlog that one-off handoffs won't fix.
How it works
- 1A schedule fires every 15 minutes.
- 2List open Front conversations with their SLA deadlines.
- 3Score each as breaching-soon, at-risk, or healthy and tally the buckets.
- 4Insert the tallied snapshot (timestamp, inbox, counts) into the Postgres ledger.
- 5Query the last several snapshots; branch if breaching-soon count is trending up across them.
- 6When the trend is rising, post a staffing alert to Slack with the slope and current backlog.
Set it up
What you configure once, before turning it on.
- 1Connect FrontShared inbox, conversations.
- 2Connect PostgresAny Postgres URL — query, write, migrate.
- 3Connect SlackChannels, DMs, threads, mentions.
- 4Set each agent's modelWe leave models unset so you pick the tier — fast + cheap, or top-quality.
- 5Tune it to your dataEdit the prompts, filters, and field mappings so it matches how your team works.
- 6Test, then turn it onRun once against a sample, confirm the output, then enable the trigger.
More Customer Support workflows
Close the loop with requesters when a Linear bug moves to Done
When a Linear issue created from a support escalation moves to Done after deploy, look up the originating Zendesk tickets and notify each requester that their reported bug is…
Reopen and notify Front conversations when their bug fix deploys
When a deploy resolves a Sentry issue, find the snoozed or closed Front conversations linked to it, reopen them, and send the customer a reply that the fix is now live.
Suggest the right Loom video by classifying Intercom message intent
Reads each new inbound Intercom conversation, classifies what the customer is trying to do, and surfaces the best-matching Loom walkthrough to the agent as an internal note.
Draft personalized fix-live replies for support to review
When a Sentry issue resolves, an agent reads each linked ticket's full thread and drafts a tailored 'your fix is live' reply per requester.
Send a tailored Loom onboarding sequence on Front first-reply
When a new customer's first email lands in Front, this picks the Loom onboarding walkthroughs matching their plan and use case, builds a friendly sequenced reply.
Article Volume-Rebound Early Warning (Datadog)
Streams support ticket-tag events into Datadog, watches for topics whose volume is reaccelerating against a decaying article.
Run it inside a business
This workflow drops into a full company template. Import the org, and this is one of the playbooks its agents run.

Run this workflow in your colony.
14-day trial. No DevOps. No Sales call. Provisioned in under a minute.
