DOCUMENT OPS

Extract contract clauses from Dropbox into a Coda obligations register

When a signed contract lands in a Dropbox folder, it pulls out key clauses (term, renewal, payment.

CategoryDocument Ops
Enginesim
Difficultyintermediate
Triggerevent
Steps5
Setup~15 min

How it runs

The automated pipeline, trigger to output.

  • TriggerNew file in Dropbox contracts folderDropboxDropbox
  • ActionDownload file and extract document textDropboxDropbox
  • ActionExtract clauses into a fixed schema with OpenAIOpenAI
  • LogicSkip files that aren't contracts (low confidence / missing fields)
  • OutputWrite obligation row to Coda registerCodaCoda

What it does

Watches a Dropbox contracts folder and turns each new signed PDF into structured obligation rows in Coda. It reads the document, has an LLM extract the clauses that create ongoing duties, and writes one register entry per contract with the party names, effective date, term length, renewal type, and notice period.

When to use it

Use it when contracts pile up in shared storage but nobody is tracking the commitments inside them. Legal ops, finance, and procurement teams use this to keep a single obligations register current without manually re-reading every agreement.

How it works

  1. 1A new file appears in the watched Dropbox contracts folder and triggers the run.
  2. 2The file content is downloaded and the document text is extracted.
  3. 3An OpenAI call parses the text into a fixed schema: counterparties, effective date, term, renewal clause, payment terms, termination rights, and governing law.
  4. 4A logic step skips non-contract files (low extraction confidence or missing party/term fields).
  5. 5The structured clauses are written as a new row in the Coda obligations register, linked back to the Dropbox path.

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 CodaDocs, packs, automations.
  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.

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