INVOICE PROCESSING

Agent that codes Front invoices to GL accounts and drafts a bill

An agent reads each Front vendor invoice, assigns GL account codes per line item using your chart of accounts and past coding history.

CategoryInvoice Processing
Enginepaperclip
Difficultyadvanced
Triggerevent
Steps5
Setup~25 min

How it runs

The automated pipeline, trigger to output.

  • TriggerVendor invoice email arrives in FrontFront
  • ActionLook up chart of accounts and coding history in NotionNotionNotion
  • LogicHold low-confidence line items for review
  • ActionWrite draft bill with proposed GL codes to NotionNotionNotion
  • OutputNotify accountant in Slack with coded vs. flagged linesSlack

What it does

Applies accounting judgment to incoming invoices. An agent reads the parsed line items from a Front invoice, looks up your chart of accounts and how similar past invoices from the same vendor were coded, then proposes a GL account and cost center for each line and assembles a draft bill an accountant can approve in one click.

When to use it

Use it when GL coding is the bottleneck in your AP close and a junior accountant spends hours mapping line items to accounts. The agent learns from prior decisions stored in your books, so coding gets more consistent over time.

How it works

  1. 1A vendor invoice email arrives in Front and triggers the agent.
  2. 2The agent extracts line items and looks up the vendor's prior coding history and the chart of accounts in Notion.
  3. 3For each line item it reasons about the right GL account and cost center, citing the precedent it used.
  4. 4A logic step holds any low-confidence line for human review instead of auto-coding.
  5. 5The agent writes a draft bill with proposed codes back to Notion and notifies the accountant in Slack with what it coded and what it flagged.

Set it up

What you configure once, before turning it on.

  1. 1
    Connect FrontShared inbox, conversations.
  2. 2
    Connect NotionPages, databases, comments.
  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.

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