INVOICE PROCESSING

Block auto-approval when an invoice exceeds its negotiated rate

Receives each invoice via webhook from your AP system, checks the total against the vendor's contracted rate stored in Postgres.

CategoryInvoice Processing
Enginesim
Difficultyadvanced
Triggerwebhook
Steps5
Setup~25 min

How it runs

The automated pipeline, trigger to output.

  • TriggerInvoice posted to approval webhookHTTP webhook
  • ActionFetch contracted rate and tolerancePostgreSQLPostgres
  • LogicCompare invoiced total to allowed rate
  • ActionEscalate over-rate variance for sign-offSlack
  • OutputReturn approve or hold decision to callerHTTP webhook

What it does

This workflow acts as a gate in your accounts-payable pipeline. When your AP or procurement tool posts an invoice to the webhook, it looks up the vendor's contracted or last-approved rate in Postgres, compares the invoiced total, and returns a structured decision: auto-approve if within terms, or hold for review if the amount exceeds the negotiated price. Held invoices are escalated so a person decides before money moves.

When to use it

Use it when invoices flow through an automated approval queue and you need a programmatic check that vendors are billing the rate you actually agreed to. Best for teams with negotiated contracts where overbilling and unauthorized increases are the real risk.

How it works

  1. 1Your AP system POSTs a new invoice payload to the webhook trigger.
  2. 2A Postgres step fetches the vendor's contracted rate and tolerance.
  3. 3A logic step compares invoiced total to the allowed rate.
  4. 4Within terms: the flow returns an approve decision to the caller.
  5. 5Over terms: it returns a hold decision and posts the variance to Slack for sign-off.

Set it up

What you configure once, before turning it on.

  1. 1
    Connect HTTP webhookTrigger any URL on agent actions.
  2. 2
    Connect PostgresAny Postgres URL — query, write, migrate.
  3. 3
    Connect SlackChannels, DMs, threads, mentions.
  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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