FINANCE

Approve and Issue Queued Proration Credit Memos

Receives an approval decision from the finance review queue and, on approval, issues the credit memo in Stripe and notifies the customer-success owner.

CategoryFinance
Enginesim
Difficultyintermediate
Triggerwebhook
Steps5
Setup~15 min

How it runs

The automated pipeline, trigger to output.

  • TriggerApproval decision webhookHTTP webhook
  • LogicBranch on approved vs rejected
  • ActionIssue Stripe credit note for the deltaStripeStripe
  • ActionRecord issued memo in SnowflakeSnowflakeSnowflake
  • OutputNotify CS owner in SlackSlack

What it does

This closes the loop on detected mischarges. When a reviewer approves or rejects a queued credit memo, this workflow acts on that decision: approved items become a real Stripe credit note against the affected invoice, rejected items are recorded with the stated reason. Either way the originating review item is resolved so nothing lingers.

When to use it

Pair this with the detection workflows once a human is in the loop on credit memos. It removes the manual step of logging into Stripe to cut credit notes and keeps the approve/reject decision, dollar amount, and reviewer all on one record.

How it works

  1. 1An approval webhook fires from your review tool with the decision payload.
  2. 2A branch splits approved from rejected decisions.
  3. 3On approval, the workflow creates a Stripe credit note for the computed delta against the customer's invoice.
  4. 4It records the issued memo and reviewer back into Snowflake for reporting.
  5. 5The CS owner is notified in Slack with the credit amount and customer.
  6. 6On rejection, the item is closed in Snowflake with the reviewer's reason and no Stripe action.

Set it up

What you configure once, before turning it on.

  1. 1
    Connect HTTP webhookTrigger any URL on agent actions.
  2. 2
    Connect StripeCustomers, subscriptions, payments.
  3. 3
    Connect SnowflakeWarehouses, queries, shares.
  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.

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