FINANCE

Agentic expense exception investigator with approver routing

On request, an agent reviews a flagged expense, gathers context from your records, judges it against the full policy, drafts a recommendation.

CategoryFinance
Enginepaperclip
Difficultyadvanced
Triggermanual
Steps5
Setup~25 min

How it runs

The automated pipeline, trigger to output.

  • TriggerFlagged expense submitted for investigation
  • ActionGather spend and context from Postgres ledgerPostgreSQLPostgres
  • LogicReason over policy intent, pattern, and budget
  • LogicDraft recommendation with rationale
  • OutputRoute case + recommendation to approver in SlackSlack

What it does

This is an agent-driven investigator for the hard expense calls that a rule engine can't settle. Given a flagged charge, it gathers the surrounding context, like the employee's recent spend, the project it was tagged to, vendor history, and the relevant policy language, then reasons about whether the exception is justified. It produces a written recommendation (approve, reject, or request more info) with its rationale and routes the case to the right approver in Slack so a human makes the final call with full context in hand.

When to use it

Use it for the gray-area exceptions that need judgment, not just a threshold: a one-off over-limit client dinner, an unusual but legitimate tool purchase, or a claim with thin documentation. Best as the second tier behind an automated policy gate, handling what deterministic rules escalate.

How it works

  1. 1A flagged expense is submitted for investigation, triggering the agent.
  2. 2The agent pulls related context from the spend ledger in Postgres and reads the applicable policy.
  3. 3It weighs the charge against policy intent, employee pattern, and project budget.
  4. 4It drafts a recommendation with reasoning and a suggested decision.
  5. 5It routes the case and its recommendation to the correct approver in Slack for the final ruling.

Set it up

What you configure once, before turning it on.

  1. 1
    Connect PostgresAny Postgres URL — query, write, migrate.
  2. 2
    Connect SlackChannels, DMs, threads, mentions.
  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.