DOCUMENT OPS

Daily Batch Redline Risk Digest to Coda and Email

Once a day, sweeps the Dropbox inbound folder for contracts received since the last run, builds a consolidated risk digest across all of them, writes per-contract rows to Coda.

CategoryDocument Ops
Enginesim
Difficultyintermediate
Triggerschedule
Steps6
Setup~15 min

How it runs

The automated pipeline, trigger to output.

  • TriggerDaily schedule fires
  • ActionList and download contracts added since last runDropboxDropbox
  • ActionRisk-score clause changes per contractOpenAI
  • LogicRank contracts by aggregate risk and build digest
  • ActionWrite per-contract rows to CodaCodaCoda
  • OutputEmail ranked risk digest to legal leadGmailGmail

What it does

On a daily schedule it collects every redlined contract added to the Dropbox folder since yesterday, extracts and risk-scores the clause changes in each, and rolls the results into one digest. Per-contract summary rows are written to Coda, and the legal lead gets an email ranking the day's contracts by aggregate risk.

When to use it

Use it when contracts trickle in throughout the day and your reviewers prefer one prioritized worklist each morning over a stream of individual notifications. It turns a noisy folder into a ranked queue.

How it works

  1. 1A daily schedule trigger fires at your chosen time.
  2. 2The flow lists Dropbox files added since the last run and downloads each one's text.
  3. 3OpenAI scores the changed clauses per contract and computes an aggregate risk level for the document.
  4. 4A logic step ranks the day's contracts from highest to lowest risk and assembles the digest.
  5. 5Per-contract rows are written to the Coda "Daily Intake" table, and a ranked summary email is sent to the legal lead.

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
    Connect GmailRead, draft, send, label.
  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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