CUSTOMER SUPPORT
Refund Velocity Guard: Auto-Hold High-Frequency Refunders
On a schedule, scans Postgres for accounts that have requested more than N refunds in a rolling window and automatically suspends their refund eligibility.
How it runs
The automated pipeline, trigger to output.
- TriggerDaily schedule
- ActionAggregate per-account refund counts in PostgresPostgres
- LogicCompare against count and amount thresholds
- ActionWrite refund-block flag to eligibility tablePostgres
- OutputPost throttled-accounts digest to SlackSlack
What it does
Catches refund abuse by velocity rather than by linkage: any account that crosses a refund-frequency threshold inside a rolling window gets its refund eligibility frozen and is queued for manual review. This stops a single account from draining refunds even when no obvious linkage exists.
When to use it
Use this as a always-on backstop when you want a deterministic, policy-driven cap on how many refunds one account can pull before a human looks. Good for teams that prefer a clear rule ("more than 3 refunds in 30 days = hold") over case-by-case judgment.
How it works
- 1A daily schedule kicks off the scan.
- 2Postgres aggregates refund counts and dollar totals per account over the rolling 30-day window.
- 3A logic step compares each account against the configured count and amount thresholds.
- 4For accounts over the line, a flag is written back to the Postgres eligibility table to block further auto-refunds.
- 5A Slack digest lists every newly throttled account with its refund count, total, and the rule it tripped.
Set it up
What you configure once, before turning it on.
- 1Connect PostgresAny Postgres URL — query, write, migrate.
- 2Connect SlackChannels, DMs, threads, mentions.
- 3Set each agent's modelWe leave models unset so you pick the tier — fast + cheap, or top-quality.
- 4Tune it to your dataEdit the prompts, filters, and field mappings so it matches how your team works.
- 5Test, 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.
