INVOICE PROCESSING

AI Agent that Investigates and Resolves Match Exceptions

For each invoice-match exception, an agent pulls context from the PO, receipt, and vendor history to diagnose the root cause and either propose a resolution or assign it…

CategoryInvoice Processing
Enginepaperclip
Difficultyadvanced
Triggerevent
Steps5
Setup~25 min

How it runs

The automated pipeline, trigger to output.

  • TriggerNew exception row created
  • ActionGather PO, receipt, vendor historyPostgreSQLPostgres
  • LogicDiagnose root cause and confidence
  • LogicSplit auto-resolvable vs. needs-human
  • OutputAnnotate fix or assign reviewer in LinearLinearLinear

What it does

Applies an investigative agent to each exception instead of just queuing it. The agent gathers the PO, the goods receipt, prior invoices from the same vendor, and any notes, then reasons about why the numbers diverge, for example a partial shipment, a known price increase, or a duplicate submission, and recommends a next action.

When to use it

Use this when your exception queue is full of items that take a human ten minutes of digging to understand. The agent does the digging and hands the reviewer a diagnosis and a recommendation, not a raw mismatch.

How it works

  1. 1A new exception row created in the queue triggers the run.
  2. 2The agent retrieves the linked PO, goods receipt, and recent vendor invoice history from Postgres.
  3. 3It reasons over the evidence to classify the likely cause and confidence level.
  4. 4A logic branch separates high-confidence auto-resolvable cases from those needing a human.
  5. 5Resolvable cases are annotated with the proposed fix; ambiguous cases are assigned to a reviewer in Linear with the full investigation attached.

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.

Run this workflow in your colony.

14-day trial. No DevOps. No Sales call. Provisioned in under a minute.