AI AGENTS

Stripe Service Credit Issuer with Slack Approval Gate

On an SLA breach, an agent sizes a service credit, posts the proposed amount to Slack for a manager click-to-approve, then issues the Stripe credit and notes it back on the ticket.

CategoryAI Agents
EngineSim + Paperclip
Difficultyadvanced
Triggerwebhook
Steps6
Setup~25 min

How it runs

The automated pipeline, trigger to output.

  • TriggerSLA breach webhook receivedHTTP webhook
  • ActionAgent computes credit from spend + severityStripeStripe
  • ActionPost credit proposal to Slack for approvalSlack
  • LogicWait on approve/deny decision
  • ActionIssue credit balance transaction in StripeStripeStripe
  • OutputPost issued-credit confirmation to SlackSlack

What it does

Turns an SLA breach into a real dollar remediation. The agent calculates a service credit proportional to the breach and the customer's monthly spend, asks a human to approve it in Slack, and on approval issues the credit directly in Stripe — closing the loop with a note on the support thread.

When to use it

Use it when your make-good is monetary and you need spend-control: credits should be computed consistently but never auto-issued without a manager signing off. Ideal for SLA contracts that promise percentage credits.

How it works

  1. 1An SLA-breach webhook arrives with the account and breach details.
  2. 2The agent computes a credit amount from breach severity and the customer's Stripe subscription value.
  3. 3It posts the proposed credit to a Slack approval channel with approve/deny actions.
  4. 4A branch waits on the human decision; denial ends the run with a logged reason.
  5. 5On approval, the flow creates the credit balance transaction in Stripe.
  6. 6It posts a confirmation back to Slack with the receipt.

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 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.

Run this workflow in your colony.

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