INVOICE PROCESSING

Match Dropbox vendor invoices against a PO sheet, line by line

Watches a Dropbox folder for new vendor invoice PDFs, extracts every line item, and validates each against your purchase-order sheet in Airtable.

CategoryInvoice Processing
Enginesim
Difficultyintermediate
Triggerevent
Steps5
Setup~15 min

How it runs

The automated pipeline, trigger to output.

  • TriggerNew invoice PDF in Dropbox inboxDropboxDropbox
  • ActionExtract line items + PO number with OpenAIOpenAI
  • ActionLook up matching PO lines in AirtableAirtableAirtable
  • LogicCompare each line; compute price/qty variance
  • OutputMark Approved or Needs Review in AirtableAirtableAirtable

What it does

When a vendor drops an invoice PDF into a shared Dropbox folder, this workflow reads it, pulls out each line item (SKU, quantity, unit price), and compares those lines to the matching purchase order in your Airtable PO sheet. It catches quantity overages, price drift, and items that were never ordered before anyone pays the bill.

When to use it

Use it when AP receives invoices as files rather than EDI, and someone is manually keying line items into a sheet to confirm them against POs. Best for teams processing dozens to hundreds of invoices a month who want a paper trail of what matched and what didn't.

How it works

  1. 1A new PDF lands in the watched Dropbox `/invoices/inbox` folder and fires the trigger.
  2. 2OpenAI extracts structured line items and the referenced PO number from the document.
  3. 3The flow looks up that PO number in Airtable and pulls its ordered lines.
  4. 4A comparison step matches each invoice line to a PO line and computes price/quantity variance.
  5. 5If every line is within tolerance, the invoice record is marked Approved in Airtable; otherwise it is marked Needs Review with the specific mismatches listed.

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 AirtableBases, tables, views, automations.
  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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