INVOICE PROCESSING

Invoice Pre-Match with Tiered Approval Routing

Parses invoices landed in Dropbox, three-way matches them against PO and receipt data in BigQuery.

CategoryInvoice Processing
Enginesim
Difficultyadvanced
Triggerevent
Steps6
Setup~25 min

How it runs

The automated pipeline, trigger to output.

  • TriggerNew invoice PDF added to DropboxDropboxDropbox
  • ActionExtract lines and total with OpenAIOpenAI
  • ActionFetch PO and receipt lines from BigQueryGoogle BigQueryBigQuery
  • LogicMatch check, then route by dollar threshold
  • ActionWrite auto-approved row for small clean matchesGoogle BigQueryBigQuery
  • OutputSend approval or exception card to MS TeamsMicrosoft Teams

What it does

Combines the three-way match with spend-based approval policy. A clean match under your auto-approve threshold posts straight to the ledger; a clean match above it goes to a manager; any mismatch goes to the exception queue regardless of amount. One workflow enforces both data accuracy and approval authority.

When to use it

Use it when approval limits depend on invoice value and you want low-value, fully-matched invoices to clear without human touch while preserving manager sign-off on larger spend.

How it works

  1. 1A new invoice PDF in Dropbox triggers the run.
  2. 2OpenAI extracts the line items and invoice total.
  3. 3BigQuery provides the matching PO lines and receipts for the three-way check.
  4. 4A logic step first confirms the match, then evaluates the total against the approval threshold.
  5. 5Clean matches under threshold write an auto-approved row to BigQuery.
  6. 6Clean matches over threshold send a manager approval card to Microsoft Teams.
  7. 7Mismatches post to the Teams exception channel with the failing lines.

Set it up

What you configure once, before turning it on.

  1. 1
    Connect DropboxFiles and folders.
  2. 2
    Connect OpenAIModels, embeddings, files.
  3. 3
    Connect BigQueryDatasets, queries, schemas.
  4. 4
    Connect Microsoft TeamsChannels, chats, files.
  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.

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