DOCUMENT OPS

Log contract clause deviations to a Notion review register

On a daily schedule, scans a Drive contracts folder, diffs clauses against approved templates with OpenAI.

CategoryDocument Ops
Enginesim
Difficultyintermediate
Triggerschedule
Steps5
Setup~15 min

How it runs

The automated pipeline, trigger to output.

  • TriggerDaily scheduled scan
  • ActionList and read contracts in Drive folderGoogle DriveGoogle Drive
  • ActionDiff clauses vs approved templates, extract deviationsOpenAI
  • LogicSkip already-logged contracts and cosmetic edits
  • OutputWrite each deviation as a Notion register rowNotionNotion

What it does

Runs once a day across all contracts in a Drive folder, compares each contract's clauses to your approved template set, and records every material deviation as a structured row in a Notion review register. Each row carries the contract name, clause type, original vs. proposed wording, and a risk rating, giving legal a single auditable queue instead of scattered email threads.

When to use it

Use it when you need a durable, trackable record of clause deviations rather than a one-off alert. Good for teams that run a clause-review workflow with status columns (open, accepted, rejected) and want history of what counterparties asked to change.

How it works

  1. 1A daily schedule starts the run.
  2. 2The Drive folder is listed and each unprocessed contract is read.
  3. 3An OpenAI step aligns clauses to approved templates and extracts each deviation with a risk rating.
  4. 4A logic step skips contracts already logged and drops cosmetic-only changes.
  5. 5Each remaining deviation is created as a Notion database row with status set to "needs review."

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.

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