CUSTOMER SUPPORT

Refund Fraud: CEO Agent Triage with Evidence Summary

An agent investigates each refund request by pulling Stripe payment history, Zendesk prior tickets, and Postgres refund records.

CategoryCustomer Support
Enginepaperclip
Difficultyadvanced
Triggerevent
Steps6
Setup~25 min

How it runs

The automated pipeline, trigger to output.

  • TriggerZendesk refund ticket createdZendeskZendesk
  • ActionAgent pulls Stripe charge, dispute, refund historyStripeStripe
  • ActionAgent reads prior Zendesk ticketsZendeskZendesk
  • ActionAgent checks Postgres for linked accountsPostgreSQLPostgres
  • LogicAgent decides clean / watch / escalate
  • OutputWrite cited verdict to ticket; Slack on escalateSlack

What it does

Gives every refund request a reasoned, evidence-backed risk write-up instead of a raw score. The agent gathers signals across systems, reasons about whether the pattern looks like genuine dissatisfaction or coordinated abuse, and hands the support agent a recommendation they can trust and explain.

When to use it

Reach for this when refund decisions are nuanced and a binary rule produces too many false positives. The agent narrative helps frontline staff approve legitimate refunds fast while spotting the subtle multi-account cases a threshold would miss.

How it works

  1. 1A Zendesk refund ticket triggers the agent.
  2. 2The agent queries Stripe for the customer's charge, dispute, and refund history.
  3. 3It pulls the customer's prior Zendesk tickets to read the complaint pattern.
  4. 4It checks Postgres for linked accounts and lifetime refund totals.
  5. 5The agent weighs the evidence and decides: clean, watch, or escalate.
  6. 6It posts a cited risk summary and recommended action as an internal Zendesk note, escalating to Slack only when the verdict is escalate.

Set it up

What you configure once, before turning it on.

  1. 1
    Connect ZendeskTickets, queues, knowledge base.
  2. 2
    Connect StripeCustomers, subscriptions, payments.
  3. 3
    Connect PostgresAny Postgres URL — query, write, migrate.
  4. 4
    Connect SlackChannels, DMs, threads, mentions.
  5. 5
    Set each agent's modelWe leave models unset so you pick the tier — fast + cheap, or top-quality.
  6. 6
    Tune it to your dataEdit the prompts, filters, and field mappings so it matches how your team works.
  7. 7
    Test, then turn it onRun once against a sample, confirm the output, then enable the trigger.

Run this workflow in your colony.

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