INVOICE PROCESSING

Emailed Invoice Discount Extractor and Triage

Watches a shared AP inbox, uses an LLM to pull payment terms and totals out of PDF invoices attached to incoming email.

CategoryInvoice Processing
Enginesim
Difficultyintermediate
Triggerevent
Steps6
Setup~15 min

How it runs

The automated pipeline, trigger to output.

  • TriggerNew email in shared AP inboxGmailGmail
  • ActionDownload attached invoice PDFGmailGmail
  • ActionExtract vendor, total, due date, and discount term with OpenAIOpenAI
  • LogicTag record as discount-eligible when a valid early-pay window exists
  • ActionWrite structured invoice to Airtable ledgerAirtableAirtable
  • OutputReply in the email thread confirming receipt and due dateGmailGmail

What it does

Most vendor invoices arrive as PDFs attached to email, with payment terms buried in fine print. This workflow reads each inbound invoice email, extracts the vendor, amount, due date, and any discount term, then files a clean structured record so nothing falls through the cracks at month end.

When to use it

Use it when invoices come into a shared accounts-payable Gmail inbox and you want them parsed and logged automatically instead of someone copying numbers by hand.

How it works

  1. 1A new email arrives in the monitored AP Gmail inbox, firing the trigger.
  2. 2The flow downloads the attached invoice PDF.
  3. 3An OpenAI extraction step reads the document and returns structured fields: vendor, invoice number, total, due date, and discount term.
  4. 4A logic branch tags the record as discount-eligible when a valid early-pay term and an open window are detected.
  5. 5It writes the structured invoice to the Airtable ledger.
  6. 6It replies in the original Gmail thread confirming receipt and the captured due date so the vendor and your team share a record.

Set it up

What you configure once, before turning it on.

  1. 1
    Connect GmailRead, draft, send, label.
  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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