FINANCE

AI Rebuttal Narrative Drafter for Stripe Disputes

Reads the order documents in Dropbox for a new Stripe dispute and uses an LLM to write a tailored rebuttal narrative matched to the chargeback reason code.

CategoryFinance
EngineSim + Paperclip
Difficultyadvanced
Triggerwebhook
Steps6
Setup~25 min

How it runs

The automated pipeline, trigger to output.

  • TriggerStripe dispute created webhookStripeStripe
  • ActionPull order evidence from DropboxDropboxDropbox
  • ActionDraft reason-specific rebuttal with OpenAIOpenAI
  • LogicValidate draft cites real evidence
  • ActionSave narrative back to Dropbox folderDropboxDropbox
  • OutputOpen Front review conversationFront

What it does

Generates the written argument that wins chargebacks. For each new dispute it gathers the order's Dropbox evidence, then prompts an LLM to draft a fact-grounded rebuttal that directly answers the specific reason code (product not received, unauthorized, not as described), citing the attached proof.

When to use it

Use it when your evidence is solid but writing persuasive, reason-specific narratives by hand is the bottleneck. The draft is staged for a human to approve, so it speeds up response time without removing judgment.

How it works

  1. 1A Stripe `charge.dispute.created` webhook triggers the flow with the reason code.
  2. 2Order documents and customer timeline are pulled from the Dropbox folder.
  3. 3An OpenAI step receives the reason code plus a summary of available evidence and drafts a structured rebuttal narrative.
  4. 4A logic check confirms the draft references at least one concrete document and contains no unsupported claims.
  5. 5The narrative is saved to the Dropbox order folder and a Front conversation is opened for a reviewer to approve and submit.

Set it up

What you configure once, before turning it on.

  1. 1
    Connect StripeCustomers, subscriptions, payments.
  2. 2
    Connect DropboxFiles and folders.
  3. 3
    Connect OpenAIModels, embeddings, files.
  4. 4
    Connect FrontShared inbox, conversations.
  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.

14-day trial. No DevOps. No Sales call. Provisioned in under a minute.