INVOICE PROCESSING

Flag recurring-vendor invoices that spike above their billing baseline

Watches incoming invoice emails from recurring vendors, compares each amount against that vendor's historical average.

CategoryInvoice Processing
Enginesim
Difficultyintermediate
Triggerevent
Steps5
Setup~15 min

How it runs

The automated pipeline, trigger to output.

  • TriggerNew invoice email in AP inboxOutlook
  • ActionParse vendor and invoice total
  • ActionFetch vendor baseline from historyGoogle BigQueryBigQuery
  • LogicAmount exceeds baseline band?
  • OutputPost spike alert to finance channelSlack

What it does

Monitors invoices arriving from your known recurring vendors and catches the ones that cost noticeably more than usual before they get paid. It compares each new invoice against a rolling baseline of that vendor's prior charges and raises a flag when the amount jumps past a tolerance threshold.

When to use it

Use this when you have dozens of monthly SaaS, utility, or service vendors and a surprise overage (extra seats, usage tiers, a price increase) routinely slips through to payment. It turns "we found out at month-end" into a same-day alert.

How it works

  1. 1An invoice email lands in the shared AP inbox in Outlook and triggers the run.
  2. 2The vendor name and total are parsed from the message and attachment.
  3. 3The vendor's trailing 6-invoice average and standard band are pulled from the BigQuery invoice history table.
  4. 4A branch checks whether the new amount exceeds the baseline by more than the configured percentage.
  5. 5If it does, a Slack alert fires to the finance channel with the vendor, the new amount, the baseline, and the delta so an approver can review before paying.

Set it up

What you configure once, before turning it on.

  1. 1
    Connect OutlookMail, calendar, contacts.
  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.

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