INVOICE PROCESSING

Block duplicate invoices from a Dropbox folder against a BigQuery ledger

Watches a shared Dropbox vendor folder for new invoices, fingerprints each one against the BigQuery payments ledger.

CategoryInvoice Processing
Enginesim
Difficultyadvanced
Triggerevent
Steps6
Setup~25 min

How it runs

The automated pipeline, trigger to output.

  • TriggerNew invoice file in Dropbox vendor folderDropboxDropbox
  • ActionParse invoice and compute fingerprint
  • ActionQuery BigQuery payments ledger for a matchGoogle BigQueryBigQuery
  • LogicBranch on match and dollar threshold
  • ActionPage on-call AP via PagerDuty for high-value duplicatesPagerDutyPagerDuty
  • OutputLog match disposition to BigQuery for auditGoogle BigQueryBigQuery

What it does

This workflow guards an AP team that receives invoices through a shared Dropbox folder and reports spend in BigQuery. Each new file is parsed, fingerprinted, and checked against the BigQuery payments ledger. Duplicates above a dollar threshold page on-call AP immediately through PagerDuty, since a high-value double payment is urgent; lower-value matches are logged for the next review cycle.

When to use it

Use it when invoices arrive as files in Dropbox and your source of truth for payments lives in BigQuery. The PagerDuty escalation is for shops where a large duplicate payment is a money-out-the-door incident that can't wait for a daily digest.

How it works

  1. 1A new file in the Dropbox vendor folder triggers the run.
  2. 2The invoice is parsed and a fingerprint is computed.
  3. 3BigQuery is queried for a matching paid invoice.
  4. 4A logic branch splits on match found and amount threshold.
  5. 5High-value duplicates trigger a PagerDuty incident to on-call AP.
  6. 6All matches and the file disposition are written back to BigQuery for audit.

Set it up

What you configure once, before turning it on.

  1. 1
    Connect DropboxFiles and folders.
  2. 2
    Connect BigQueryDatasets, queries, schemas.
  3. 3
    Connect PagerDutyIncidents, on-call, escalations.
  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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