CUSTOMER SUPPORT

Refund-vs-dispute pre-check on new Stripe disputes

When Stripe opens a dispute, this gathers the charge, usage, and prior refund history, decides whether a proactive refund is cheaper than fighting it.

CategoryCustomer Support
Enginesim
Difficultyadvanced
Triggerevent
Steps5
Setup~25 min

How it runs

The automated pipeline, trigger to output.

  • TriggerStripe dispute created eventStripeStripe
  • ActionFetch dispute and original charge detailsStripeStripe
  • ActionQuery usage and refund history in PostgresPostgreSQLPostgres
  • LogicCompare proactive refund vs contesting cost
  • OutputPost recommendation to Slack disputes channelSlack

What it does

When a chargeback dispute opens in Stripe, it builds the case file your team needs to decide fast: refund proactively to avoid dispute fees, or contest with evidence. It pulls the disputed charge, the customer's actual product usage, and whether they've been refunded before, then recommends the cheaper path and posts it for the disputes team.

When to use it

Use it when chargebacks are eating into margin and you want a consistent, cost-aware first call on every new dispute instead of reacting case by case under the response deadline.

How it works

  1. 1A `charge.dispute.created` event from Stripe triggers the flow.
  2. 2Stripe is queried for the dispute amount, reason code, and original charge details.
  3. 3Postgres returns the customer's usage and prior refund history.
  4. 4A logic step compares the dispute fee plus loss risk against a proactive refund and picks the lower-cost action.
  5. 5The recommendation and supporting evidence are posted to a Slack disputes channel for sign-off.

Set it up

What you configure once, before turning it on.

  1. 1
    Connect StripeCustomers, subscriptions, payments.
  2. 2
    Connect PostgresAny Postgres URL — query, write, migrate.
  3. 3
    Connect SlackChannels, DMs, threads, mentions.
  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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