FINANCE

Investigate a flagged refund cohort with an AI agent and file a packaged case

Takes a flagged merchant cohort, has an agent gather the underlying refunds, charges, and customer overlap from Stripe and Snowflake, write a plain-English findings memo.

CategoryFinance
Enginepaperclip
Difficultyadvanced
Triggerevent
Steps6
Setup~25 min

How it runs

The automated pipeline, trigger to output.

  • TriggerCohort flagged for investigation
  • ActionAgent pulls refunds and original charges from StripeStripeStripe
  • ActionAgent queries Snowflake for history and customer overlapSnowflakeSnowflake
  • LogicAgent classifies pattern and drafts findings memo
  • ActionOpen Monday case with evidence bundlemonday.com
  • OutputNotify assigned analyst in SlackSlack

What it does

Turns a raw anomaly flag into an investigation-ready case. An agent pulls the relevant refunds and original charges, looks for shared customers, repeated amounts, and timing clusters, then drafts a short narrative explaining what the pattern most likely is and what to check next.

When to use it

Use this when analysts spend the first 30 minutes of every review just assembling context. Hand the agent a flagged cohort and it returns the assembled evidence and a hypothesis, so the human starts at judgment instead of data gathering.

How it works

  1. 1Triggered when a cohort is flagged (manually or by an upstream detector).
  2. 2The agent queries Stripe for the cohort's refunds and matching original charges.
  3. 3The agent queries Snowflake for historical context and customer overlap.
  4. 4The agent reasons over the data to classify the pattern and draft a findings memo.
  5. 5Create a Monday case with the memo, the evidence table, and a recommended disposition.
  6. 6Notify the assigned analyst in Slack with the case link.

Set it up

What you configure once, before turning it on.

  1. 1
    Connect StripeCustomers, subscriptions, payments.
  2. 2
    Connect SnowflakeWarehouses, queries, shares.
  3. 3
    Connect monday.comVisual work management for teams.
  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.

Run this workflow in your colony.

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