INVOICE PROCESSING

Build a Three-Way Match Exception Queue in Airtable

On a schedule, joins purchase orders, goods receipts, and invoices from Postgres, flags any line where quantity or amount disagrees across the three.

CategoryInvoice Processing
Enginesim
Difficultyintermediate
Triggerschedule
Steps5
Setup~15 min

How it runs

The automated pipeline, trigger to output.

  • TriggerNightly schedule fires
  • ActionQuery joined PO + receipt + invoice linesPostgreSQLPostgres
  • LogicCompare qty and price across all three
  • LogicDrop clean matches, keep exceptions
  • OutputUpsert exceptions into Airtable review queueAirtableAirtable

What it does

Reconciles every open invoice against its purchase order and the warehouse receipt, then surfaces only the lines that fail the three-way match into a single Airtable queue your AP team works from. Clean matches are auto-cleared and never bother a human.

When to use it

Use this when invoices, POs, and receipts all live in your ERP/Postgres but AP still eyeballs matches in spreadsheets. It replaces the manual reconcile with a nightly job that only escalates true exceptions.

How it works

  1. 1A nightly schedule fires the run.
  2. 2Postgres returns each invoice line joined to its PO line and the matching receipt line by PO number and SKU.
  3. 3A logic step compares ordered vs received vs billed quantity and PO unit price vs invoiced price, classifying each line as matched, price variance, quantity variance, or missing receipt.
  4. 4Matched lines are dropped; only exceptions continue.
  5. 5Each exception is upserted into the Airtable AP Review table with the variance type, the three source values, and the dollar delta.
  6. 6A summary count is written back so the queue shows how many opened today.

Set it up

What you configure once, before turning it on.

  1. 1
    Connect PostgresAny Postgres URL — query, write, migrate.
  2. 2
    Connect AirtableBases, tables, views, automations.
  3. 3
    Set each agent's modelWe leave models unset so you pick the tier — fast + cheap, or top-quality.
  4. 4
    Tune it to your dataEdit the prompts, filters, and field mappings so it matches how your team works.
  5. 5
    Test, then turn it onRun once against a sample, confirm the output, then enable the trigger.

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