agent hive

INVOICE PROCESSING

AI intake agent that extracts, converts, and routes emailed multi-currency invoices

Reads invoices arriving in a shared inbox, uses an AI agent to extract vendor, currency, and totals, converts to base currency.

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

How it runs

The automated pipeline, trigger to output.

  • TriggerNew invoice email in shared inboxGmailGmail
  • ActionAI extracts vendor, currency, amount, dateOpenAI
  • ActionFetch FX rate and compute base totalHTTP webhook
  • LogicPick approver by vendor and converted amount
  • ActionInsert normalized invoice into Postgres stagingPostgreSQLPostgres
  • OutputSend approval request to owner in SlackSlack

What it does

This agent-driven workflow handles unstructured invoices that arrive by email in any layout or currency. It extracts the key fields, normalizes the total to your reporting currency, decides the correct approval owner by vendor and amount, and stages a clean record for the ledger.

When to use it

Use it when invoices come as PDFs or inline email in inconsistent formats and currencies, and you want hands-off extraction plus FX normalization plus routing without building rigid parsers per vendor.

How it works

  1. 1A new email in the shared finance inbox triggers the workflow.
  2. 2An AI extraction step reads the message and attachment to pull vendor, currency, amount, and invoice date.
  3. 3An HTTP call fetches the FX rate for the invoice date and the base-currency total is computed.
  4. 4A logic step selects the approver based on vendor and converted amount thresholds.
  5. 5The normalized invoice is inserted into Postgres staging and an approval request is sent to the chosen owner in Slack.

Set it up

What you configure once, before turning it on.

  1. 1
    Connect GmailRead, draft, send, label.
  2. 2
    Connect OpenAIModels, embeddings, files.
  3. 3
    Connect HTTP webhookTrigger any URL on agent actions.
  4. 4
    Connect PostgresAny Postgres URL — query, write, migrate.
  5. 5
    Connect SlackChannels, DMs, threads, mentions.
  6. 6
    Set each agent's modelWe leave models unset so you pick the tier — fast + cheap, or top-quality.
  7. 7
    Tune it to your dataEdit the prompts, filters, and field mappings so it matches how your team works.
  8. 8
    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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