DOCUMENT OPS

Flag contract redline deviations against the approved playbook

When a counterparty uploads a redlined contract to a Drive folder, it extracts every clause, diffs each against your approved playbook positions.

CategoryDocument Ops
Enginesim
Difficultyintermediate
Triggerevent
Steps5
Setup~15 min

How it runs

The automated pipeline, trigger to output.

  • TriggerNew redlined contract in Drive folderGoogle DriveGoogle Drive
  • ActionRead document and extract clausesOpenAI
  • ActionDiff each clause against playbook positionsOpenAI
  • LogicKeep only clauses that deviate
  • OutputPublish deviation report to NotionNotionNotion

What it does

It watches a shared Drive folder for incoming redlined contracts, pulls the clause text out of each one, compares every clause against your standard playbook positions, and writes a structured deviation report. Each clause is scored as on-playbook, minor deviation, or unacceptable so reviewers triage instead of reading line by line.

When to use it

Use it when counterparties return redlines and your team re-reads the whole document every time. It is built for legal ops and deal desks running a known playbook of acceptable fallback positions across NDAs, MSAs, and order forms.

How it works

  1. 1A new redlined document lands in the monitored Google Drive folder and triggers the run.
  2. 2The file content is read and the model extracts each clause with its heading and text.
  3. 3Each extracted clause is matched to the corresponding playbook position and the model classifies the deviation severity with a short rationale.
  4. 4A logic step filters out clauses that match the playbook so only deviations carry forward.
  5. 5A Notion page is created summarizing every flagged clause, its severity, and the playbook gap for reviewer sign-off.

Set it up

What you configure once, before turning it on.

  1. 1
    Connect Google DriveDocs, sheets, slides, files.
  2. 2
    Connect OpenAIModels, embeddings, files.
  3. 3
    Connect NotionPages, databases, comments.
  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.

Run this workflow in your colony.

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