INVOICE PROCESSING

Flag Statement Invoices Missing From the AP System on File Upload

When a vendor statement is uploaded to Google Drive, this finds every invoice the vendor billed that has no record in your Postgres AP system and creates a follow-up task…

CategoryInvoice Processing
Enginesim
Difficultybeginner
Triggerevent
Steps5
Setup~5 min

How it runs

The automated pipeline, trigger to output.

  • TriggerStatement file uploaded to DriveGoogle DriveGoogle Drive
  • ActionParse statement into invoice numbersOpenAI
  • ActionLook up each invoice in Postgres AP tablePostgreSQLPostgres
  • LogicKeep only invoices with no AP match
  • OutputCreate Asana follow-up task per missing invoiceAsanaAsana

What it does

Focuses on one decision: which invoices does the vendor say we owe that we have no trace of? On upload, it parses the statement, checks each invoice number against the AP invoices table in Postgres, and isolates the ones with zero match. Those become actionable follow-ups so AP can either obtain the missing invoice copy or dispute the line, instead of silently letting it slip into aging.

When to use it

Reach for this when missing invoices, not amount disputes, are your main reconciliation headache, and your AP records live in Postgres. It is a lightweight, single-purpose complement to a fuller tie-out.

How it works

  1. 1A new file landing in the Drive statements folder triggers the flow.
  2. 2The statement is read and parsed into invoice numbers and amounts.
  3. 3Postgres is queried for each invoice number in the AP table.
  4. 4A filter keeps only invoices with no matching AP record.
  5. 5For each missing invoice, an Asana task is created tagging the AP owner with vendor, invoice number, and amount.

Set it up

What you configure once, before turning it on.

  1. 1
    Connect Google DriveDocs, sheets, slides, files.
  2. 2
    Connect OpenAIModels, embeddings, files.
  3. 3
    Connect PostgresAny Postgres URL — query, write, migrate.
  4. 4
    Connect AsanaTasks, projects, milestones — everywhere.
  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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