DOCUMENT OPS

Extract clauses from new signed contracts into an Airtable obligations register

Watches a Dropbox folder for newly signed contracts, uses an LLM to pull key clauses and obligations, and writes each one as a structured row in an Airtable obligations register.

CategoryDocument Ops
Enginesim
Difficultyintermediate
Triggerevent
Steps5
Setup~15 min

How it runs

The automated pipeline, trigger to output.

  • TriggerNew signed contract added to Dropbox folderDropboxDropbox
  • ActionDownload file and extract PDF textDropboxDropbox
  • ActionExtract structured clauses and obligations with OpenAIOpenAI
  • LogicDrop boilerplate and rows missing party or obligation
  • OutputWrite each obligation as a row in Airtable registerAirtableAirtable

What it does

Turns freshly signed PDFs landing in Dropbox into a structured, queryable obligations register in Airtable. Each contract is parsed into discrete obligations — payment terms, deliverables, SLAs, liability caps, termination notice — with the owning party and any deadline attached.

When to use it

Use it when your legal or ops team saves countersigned agreements to a shared Dropbox folder and you need a living register instead of re-reading PDFs every quarter. Ideal for teams without a dedicated CLM tool.

How it works

  1. 1A new file lands in the monitored Dropbox `/Signed Contracts` folder and triggers the run.
  2. 2The file is downloaded and its text extracted from the PDF.
  3. 3An OpenAI call extracts a structured list of clauses: type, summary, obligated party, due/notice date, and source page.
  4. 4A logic step filters out boilerplate and drops rows missing both a party and an obligation.
  5. 5Each remaining obligation is written as a row in the Airtable register, linked to a parent contract record.

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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