DOCUMENT OPS

Agent-driven contract intake: file, register, and route exceptions

An agent processes each new Dropbox contract end to end — splitting, classifying, filing by counterparty, logging to Airtable.

CategoryDocument Ops
Enginepaperclip
Difficultyadvanced
Triggerevent
Steps5
Setup~25 min

How it runs

The automated pipeline, trigger to output.

  • TriggerNew PDF in Dropbox intake folderDropboxDropbox
  • ActionRead, split, and classify with OpenAIOpenAI
  • LogicCounterparty match confidence high?
  • ActionFile in Dropbox + log to AirtableAirtableAirtable
  • OutputEscalate ambiguous cases to Slack for decisionSlack

What it does

Runs the full contract-intake desk as one autonomous agent. For each signed PDF in Dropbox it decides how to split the file, identifies the counterparty and type, files the documents into the right folders, records the contract in Airtable, and — when something does not fit the rules — pauses to ask a human in Slack instead of guessing.

When to use it

Use it when intake is varied enough that a fixed pipeline breaks: unknown counterparties, novel contract types, bundles that split unpredictably. The agent handles the routine cases automatically and routes only the genuine edge cases to a person.

How it works

  1. 1A new PDF in the Dropbox intake folder triggers the agent.
  2. 2The agent reads the document, splitting bundles and classifying counterparty and contract type via OpenAI.
  3. 3A logic step assesses confidence in the counterparty match.
  4. 4On high confidence, the agent files the documents in Dropbox and logs a row to Airtable.
  5. 5On low confidence or an unrecognized type, the output posts the case to Slack and waits for a human to confirm the destination before filing.

Set it up

What you configure once, before turning it on.

  1. 1
    Connect DropboxFiles and folders.
  2. 2
    Connect OpenAIModels, embeddings, files.
  3. 3
    Connect AirtableBases, tables, views, automations.
  4. 4
    Connect SlackChannels, DMs, threads, mentions.
  5. 5
    Set each agent's modelWe leave models unset so you pick the tier — fast + cheap, or top-quality.
  6. 6
    Tune it to your dataEdit the prompts, filters, and field mappings so it matches how your team works.
  7. 7
    Test, then turn it onRun once against a sample, confirm the output, then enable the trigger.

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