DOCUMENT OPS

Dropbox Inbound Redline to Clause-Comparison Matrix in Coda

When a counterparty drops a redlined contract into a Dropbox folder, this extracts each changed clause, compares it against your standard language.

CategoryDocument Ops
Enginesim
Difficultyintermediate
Triggerevent
Steps5
Setup~15 min

How it runs

The automated pipeline, trigger to output.

  • TriggerNew contract file added to Dropbox inbound folderDropboxDropbox
  • ActionDownload file and extract document textDropboxDropbox
  • ActionSegment clauses and pair against standard libraryOpenAI
  • LogicKeep changed clauses only and score risk
  • OutputWrite clause-comparison matrix rows to CodaCodaCoda

What it does

Watches a Dropbox intake folder for inbound redlined contracts. For each new file, it pulls the document text, isolates the clauses that differ from your playbook standard, and produces a structured comparison: standard language, counterparty language, what changed, and a risk flag (low/medium/high). The result lands as rows in a Coda table your legal reviewers triage from.

When to use it

Use it when counterparties send marked-up versions of your paper and a human is currently re-reading the whole document to find what moved. It surfaces only the deltas that matter so review starts at the risk, not at page one.

How it works

  1. 1A new file appears in the Dropbox `/contracts/inbound` folder and fires the trigger.
  2. 2The flow downloads the file and extracts its full text.
  3. 3An OpenAI extraction step segments the document into named clauses (indemnity, liability cap, termination, governing law, and so on) and pairs each against your standard clause library.
  4. 4A logic step keeps only clauses that changed and scores each delta for risk based on deviation from your fallback positions.
  5. 5Each flagged clause is written as a row in the Coda "Redline Review" table with the risk flag, the diff, and a suggested response.

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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