FINANCE

Deferred-Revenue Cutoff Anomaly Investigation Agent

An agent that investigates each flagged cutoff mismatch by pulling the Stripe invoice, Snowflake schedule, and contract terms.

CategoryFinance
Enginepaperclip
Difficultyadvanced
Triggerevent
Steps5
Setup~25 min

How it runs

The automated pipeline, trigger to output.

  • TriggerNew exception row created in AirtableAirtableAirtable
  • ActionFetch invoice and line items from StripeStripeStripe
  • ActionQuery schedule history and contract metadata in SnowflakeSnowflakeSnowflake
  • LogicReason over dates and policy to recommend period treatment
  • OutputWrite narrative and recommendation back to AirtableAirtableAirtable

What it does

For every flagged cutoff exception, an agent gathers the full context — the Stripe invoice, the Snowflake deferred-revenue schedule, and the contract service dates — reasons about why the periods disagree, and drafts a plain-English explanation plus a recommended recognition treatment.

When to use it

When the volume of flagged exceptions is too high for the controller to research each one by hand and you want a first-pass analyst writeup attached to every item before review.

How it works

  1. 1A new row in the Airtable exceptions table triggers the agent.
  2. 2The agent fetches the related invoice and line items from Stripe.
  3. 3It queries Snowflake for the schedule history and any contract metadata.
  4. 4The agent reasons over service period, billing date, and policy to determine the correct period, citing the evidence it used.
  5. 5It writes the narrative and recommended treatment back to the Airtable row and sets a review status for the controller.

Set it up

What you configure once, before turning it on.

  1. 1
    Connect AirtableBases, tables, views, automations.
  2. 2
    Connect StripeCustomers, subscriptions, payments.
  3. 3
    Connect SnowflakeWarehouses, queries, shares.
  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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