INVOICE PROCESSING

Invoice Duplicate and Anomaly Screen Before Matching

Screens every new invoice for duplicates, mismatched vendor banking details, and out-of-pattern amounts before it enters the three-way match.

CategoryInvoice Processing
Enginepaperclip
Difficultyadvanced
Triggerevent
Steps5
Setup~25 min

How it runs

The automated pipeline, trigger to output.

  • TriggerNew invoice row inserted in PostgresPostgreSQLPostgres
  • ActionPull payment history and vendor masterPostgreSQLPostgres
  • LogicAgent screens for duplicates and anomalies
  • ActionRelease clean invoices to match queuePostgreSQLPostgres
  • OutputOpen Linear review task for suspect invoicesLinearLinear

What it does

Adds a fraud-and-duplicate gate ahead of matching. An agent reviews each new invoice against payment history and vendor master data, looking for repeat invoice numbers, changed bank accounts, round-number anomalies, and vendors not on file, then explains anything it flags.

When to use it

When you want a safeguard against duplicate payments and invoice fraud before invoices flow into the automated match-and-pay pipeline, without a human screening every one by hand.

How it works

  1. 1A new invoice row in Postgres fires the trigger.
  2. 2The agent pulls recent payments and the vendor master record for context.
  3. 3It reasons over duplicate invoice numbers, altered banking details, amount anomalies, and unknown vendors.
  4. 4A logic step splits clean invoices from suspect ones.
  5. 5Clean invoices are released into the matching queue in Postgres.
  6. 6Suspect invoices are placed on hold and a Linear task is created with the agent's reasoning and the specific risk signals for an AP analyst to review.

Set it up

What you configure once, before turning it on.

  1. 1
    Connect PostgresAny Postgres URL — query, write, migrate.
  2. 2
    Connect LinearIssues, projects, cycles, triage.
  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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