DOCUMENT OPS

Extract contract clauses from new Dropbox uploads into a risk register

When a contract lands in a Dropbox folder, it pulls the text, extracts key clauses (liability, indemnity, termination, auto-renewal), scores each for risk.

CategoryDocument Ops
Enginesim
Difficultyintermediate
Triggerevent
Steps5
Setup~15 min

How it runs

The automated pipeline, trigger to output.

  • TriggerNew file added to Dropbox contracts folderDropboxDropbox
  • ActionDownload file and extract document textDropboxDropbox
  • ActionExtract named clauses and score each for riskOpenAI
  • LogicFlag for review if any clause is high risk
  • OutputAppend contract and clause risks as a Coda register rowCodaCoda

What it does

Watches a Dropbox "Incoming Contracts" folder and turns every new PDF or DOCX into a structured, reviewable entry. It reads the document, isolates the clauses that matter most to legal and procurement, assigns a risk level to each, and writes one register row per contract so nothing sits unreviewed in a shared drive.

When to use it

Use it when vendors or counterparties email signed agreements that get dropped into a shared Dropbox folder and a person has to manually skim each one. Good for ops, procurement, or a small legal team that wants triage before a human reads the full paper.

How it works

  1. 1A new file in the watched Dropbox folder fires the trigger.
  2. 2The file contents are downloaded and the document text is extracted.
  3. 3OpenAI extracts named clauses (liability cap, indemnity, termination, auto-renewal, governing law) and rates each low/medium/high risk with a one-line rationale.
  4. 4A logic step checks whether any clause scored high.
  5. 5The contract, its clauses, and risk levels are appended as a new row in the Coda risk register, flagged for review when high-risk clauses are present.

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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