DOCUMENT OPS

Nightly Batch Redline Sweep to Airtable Deal Register

Each night it scans a Google Drive folder for contracts that gained a new version that day, diffs each against its prior version.

CategoryDocument Ops
Enginesim
Difficultyintermediate
Triggerschedule
Steps5
Setup~15 min

How it runs

The automated pipeline, trigger to output.

  • TriggerNightly schedule fires
  • ActionList Drive contracts with a new version todayGoogle DriveGoogle Drive
  • LogicIterate each changed contract; pair new with prior version
  • ActionReconcile clauses and extract material deltasOpenAI
  • OutputUpsert per-deal change record into Airtable registerAirtableAirtable

What it does

On a nightly schedule it sweeps a Google Drive contracts workspace for any agreement that received a new version that day. For each one it pairs the new version with the prior, reconciles clauses, and isolates the material changes. It writes a per-deal summary into an Airtable deal register, one record per contract with delta count, materiality breakdown, and links, so the team starts the day with a complete picture of overnight movement.

When to use it

Use it when you manage a portfolio of simultaneously negotiating deals and want a batched morning digest instead of real-time pings. Ideal for deal operations teams that already track agreements in Airtable and want change activity rolled into the same register.

How it works

  1. 1A nightly schedule triggers the flow.
  2. 2The flow lists Google Drive contracts that gained a new version in the last day.
  3. 3A logic step iterates each changed contract and pairs new with prior version.
  4. 4An OpenAI step reconciles clauses and extracts material deltas per contract.
  5. 5It upserts a per-deal record into the Airtable register with the change summary.

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.

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