INVOICE PROCESSING

Agent-Classify Ambiguous Invoice Lines to Budget Categories

Picks up invoice lines that rule-based mapping couldn't resolve, has an agent reason over vendor history and the GL chart of accounts to propose a category with rationale.

CategoryInvoice Processing
EngineSim + Paperclip
Difficultyadvanced
Triggerschedule
Steps6
Setup~25 min

How it runs

The automated pipeline, trigger to output.

  • TriggerScheduled sweep of uncategorized queue
  • ActionLoad pending lines and vendor historyPostgreSQLPostgres
  • ActionAgent proposes category, rationale, confidenceOpenAI
  • LogicBranch by confidence score
  • ActionFile high-confidence picks with audit rationalePostgreSQLPostgres
  • OutputEscalate ambiguous lines to controller SlackSlack

What it does

For invoice lines that deterministic rules leave uncategorized, this agent-driven workflow reads the line description, the vendor's prior categorizations, and the GL chart of accounts, then proposes the best-fit budget category with a written rationale and confidence. High-confidence proposals are auto-filed; ambiguous ones are escalated to a controller.

When to use it

Use this as the second pass behind your rule engine, when a meaningful share of lines are messy free-text descriptions that rules can't catch but a reasoning agent can resolve from context.

How it works

  1. 1A schedule sweeps the uncategorized queue at a set interval.
  2. 2The flow loads each pending line plus the vendor's historical mappings from Postgres.
  3. 3An agent reasons over the line and the GL chart to propose a category, rationale, and confidence score.
  4. 4A branch routes by confidence.
  5. 5High-confidence proposals are written to the categorized table with the rationale stored for audit.
  6. 6Low-confidence proposals post to the controller's Slack with the agent's reasoning for a quick approve or correct.

Set it up

What you configure once, before turning it on.

  1. 1
    Connect PostgresAny Postgres URL — query, write, migrate.
  2. 2
    Connect OpenAIModels, embeddings, files.
  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.

Run this workflow in your colony.

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