FINANCE

CEO agent reviews card charges against spend policy and flags violations

An agent reviews each new card charge against your written spend policy, drafts a compliant GL memo when it passes.

CategoryFinance
Enginepaperclip
Difficultyadvanced
Triggerevent
Steps5
Setup~25 min

How it runs

The automated pipeline, trigger to output.

  • TriggerNew Stripe card transactionStripeStripe
  • ActionPull vendor history and category limits from BigQueryGoogle BigQueryBigQuery
  • LogicAgent evaluates charge against spend policy
  • LogicBranch: compliant memo vs. policy violation
  • OutputPost memo or escalate violation to finance SlackSlack

What it does

Goes beyond coding to judgment: an agent reads each card charge alongside your spend policy, vendor history, and category limits, then either drafts a clean GL-coded memo for compliant charges or escalates the ones that look like policy breaches — over-limit, out-of-category, or duplicate spend — with a written rationale.

When to use it

Use this when memo enrichment isn't enough and you want a reasoning layer that enforces spend policy on every transaction. Best for orgs with a real expense policy that today gets enforced only by spot-checks at close.

How it works

  1. 1A new Stripe card transaction fires the trigger.
  2. 2The agent pulls vendor history and category limits from BigQuery for context.
  3. 3The agent evaluates the charge against the written spend policy and decides compliant vs. violation.
  4. 4A branch routes the outcome: compliant charges get a drafted GL memo, violations get an escalation.
  5. 5Compliant memos post to the controller channel; flagged charges escalate to a finance Slack channel with the agent's reasoning.

Set it up

What you configure once, before turning it on.

  1. 1
    Connect StripeCustomers, subscriptions, payments.
  2. 2
    Connect BigQueryDatasets, queries, schemas.
  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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