DOCUMENT OPS

Log every contract deviation to an Airtable deal tracker

When a redline is reviewed, it extracts the deviating clauses and writes one row per deviation to an Airtable base tagged by deal, clause type, and severity.

CategoryDocument Ops
Enginesim
Difficultyintermediate
Triggerevent
Steps5
Setup~15 min

How it runs

The automated pipeline, trigger to output.

  • TriggerReviewed redline added to DriveGoogle DriveGoogle Drive
  • ActionExtract deviating clausesOpenAI
  • ActionNormalize deviations into recordsOpenAI
  • LogicDeduplicate against existing deal rows
  • OutputWrite rows to Airtable deal trackerAirtableAirtable

What it does

It turns each reviewed redline into structured rows in an Airtable tracker: one record per playbook deviation, tagged with the deal name, clause type, severity, and the proposed-versus-standard language. Over time this becomes a queryable history of which clauses counterparties push on most.

When to use it

Use it when leadership wants analytics on negotiation patterns, not just per-deal flags. It suits legal ops teams that need to report on recurring concessions, benchmark fallback positions, or feed renewal strategy.

How it works

  1. 1A redline is added to the reviewed-contracts Drive folder, triggering the run.
  2. 2The document is read and the model extracts each clause that deviates from the playbook.
  3. 3Each deviation is normalized into a record with deal, clause type, severity, and standard-versus-proposed language.
  4. 4A logic step deduplicates against existing rows for the same deal so re-reviews update rather than duplicate.
  5. 5Records are written to the Airtable deal tracker for reporting and trend analysis.

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 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.

Run this workflow in your colony.

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