INVOICE PROCESSING

Catch Unexpected Early Vendor Bills Arriving in Outlook

Scans incoming vendor invoices in Outlook, compares each against the vendor's normal billing schedule.

CategoryInvoice Processing
Enginesim
Difficultyintermediate
Triggerevent
Steps5
Setup~15 min

How it runs

The automated pipeline, trigger to output.

  • TriggerNew invoice email arrives in AP Outlook inboxOutlook
  • ActionExtract vendor, date, and amount with OpenAIOpenAI
  • ActionMatch vendor cadence record in PostgresPostgreSQLPostgres
  • LogicFlag bills arriving earlier than expected window
  • OutputForward flagged early bill to AP reviewer in OutlookOutlook

What it does

Monitors a shared AP mailbox for inbound vendor invoices. For each one, it uses an LLM to extract the vendor, invoice date, and amount, then compares the arrival against that vendor's known cadence in Postgres. If a bill shows up materially earlier than its expected window, it gets flagged as an anomaly worth a human check — a common signal of duplicate billing, a billing-cycle change, or fraud.

When to use it

Use it when early or off-cycle invoices are a real risk: you want a gate that questions any recurring bill arriving ahead of schedule before it lands in the payment run.

How it works

  1. 1New email arriving in the AP Outlook inbox triggers the flow.
  2. 2OpenAI extracts vendor name, invoice date, and amount from the message and attachment.
  3. 3Match the vendor to its cadence record in Postgres.
  4. 4Branch: flag invoices arriving earlier than the expected window or duplicating a recent bill.
  5. 5Reply or forward in Outlook to the AP reviewer with the early-bill flag and the expected-vs-actual dates.

Set it up

What you configure once, before turning it on.

  1. 1
    Connect OutlookMail, calendar, contacts.
  2. 2
    Connect OpenAIModels, embeddings, files.
  3. 3
    Connect PostgresAny Postgres URL — query, write, migrate.
  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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