CUSTOMER SUPPORT

Refund decision brief for new Zendesk refund tickets

On a new Zendesk ticket about a refund, an agent assembles billing status from Stripe, usage and refund history from Postgres.

CategoryCustomer Support
Enginepaperclip
Difficultyintermediate
Triggerevent
Steps5
Setup~15 min

How it runs

The automated pipeline, trigger to output.

  • TriggerNew refund ticket created in ZendeskZendeskZendesk
  • ActionFetch Stripe billing status and invoicesStripeStripe
  • ActionQuery usage and prior refunds in PostgresPostgreSQLPostgres
  • LogicForm refund recommendation from policy
  • OutputWrite eligibility brief as private Zendesk commentZendeskZendesk

What it does

Gives Zendesk agents a ready-made refund brief the moment a refund ticket lands. An agent reasons over the customer's Stripe billing state, recent usage, and refund track record, then drafts a private comment that states the recommended decision, the policy reasons behind it, and the numbers that matter — so the human reply is fast and defensible.

When to use it

Use it when refunds come through Zendesk and you want every agent to start from the same complete picture rather than reconstructing it ticket by ticket.

How it works

  1. 1A new Zendesk ticket matching your refund triggers (form or tag) starts the flow.
  2. 2The agent fetches Stripe subscription status, last invoice, and payment health for the requester.
  3. 3It queries Postgres for usage in the current period and prior refund events.
  4. 4The agent weighs the evidence against your refund policy and forms a recommendation.
  5. 5It writes a structured eligibility brief as a private internal comment on the Zendesk ticket.

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
    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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