DOCUMENT OPS

Counterparty Deviation Tracker for Dropbox Contract Drafts

Compares each redlined draft in Dropbox against your standard template clauses and logs every deviation from approved language to an Airtable tracker.

CategoryDocument Ops
Enginesim
Difficultyadvanced
Triggerevent
Steps5
Setup~25 min

How it runs

The automated pipeline, trigger to output.

  • TriggerRedlined draft added to DropboxDropboxDropbox
  • ActionLoad the matching standard templateDropboxDropbox
  • ActionCompare draft to template and describe deviationsOpenAI
  • LogicScore each deviation against the fallback playbook
  • OutputLog deviations and dispositions to AirtableAirtableAirtable

What it does

Rather than diffing a contract against its own prior version, this workflow diffs each Dropbox draft against your firm's standard template. It identifies where the counterparty deviated from your approved language and records every deviation in an Airtable tracker, marking which ones still sit inside your pre-approved fallback positions and which need escalation.

When to use it

Use it when you negotiate from a house paper or playbook and want a running record of how far each counterparty pushed. It builds the dataset for playbook analytics and shows where your standard clauses get challenged most.

How it works

  1. 1A redlined draft added to Dropbox triggers the run.
  2. 2The workflow loads the matching standard template for that contract type.
  3. 3An OpenAI step compares the draft to the template clause by clause and describes each deviation.
  4. 4A logic step scores each deviation against your fallback playbook: within-policy, needs-review, or out-of-policy.
  5. 5Every deviation is written to an Airtable row with clause, deviation text, and disposition.
  6. 6The tracker surfaces out-of-policy items at the top for the negotiator.

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
    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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