INVOICE PROCESSING

Nightly Re-Submission Sweep and Digest

Runs on a schedule to scan the day's posted invoices across Postgres and Airtable for clusters that share a fingerprint, then posts a ranked duplicate-risk digest to AP leadership.

CategoryInvoice Processing
Enginesim
Difficultyintermediate
Triggerschedule
Steps6
Setup~15 min

How it runs

The automated pipeline, trigger to output.

  • TriggerNightly schedule
  • ActionPull day's posted invoices from ledgerPostgreSQLPostgres
  • ActionPull recent Airtable intake rowsAirtableAirtable
  • LogicCluster by fingerprint, keep multi-member groups
  • ActionRank clusters by dollar exposure and recency
  • OutputPost ranked duplicate-risk digest to SlackSlack

What it does

A scheduled batch sweep that looks back over recent invoice activity and clusters records that share the same vendor-amount-number fingerprint across both your Postgres ledger and Airtable intake. It surfaces duplicate clusters that single-record checks miss and sends AP leadership a ranked digest each night so patterns get caught before the next pay run.

When to use it

Use this as a safety net on top of real-time guards, especially when invoices arrive from many sources over a day. It catches slow-burn duplicates that crossed system boundaries and gives managers a daily risk picture.

How it works

  1. 1A nightly schedule triggers the sweep.
  2. 2The flow pulls the day's posted invoices from the Postgres ledger and recent Airtable intake rows.
  3. 3It groups records by fingerprint and identifies clusters with more than one member.
  4. 4It ranks clusters by total dollar exposure and recency.
  5. 5It assembles a digest of the top risk clusters with direct links.
  6. 6The digest is posted to the AP leadership Slack channel.

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
    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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