DOCUMENT OPS

Archive signed NDAs from Dropbox with extracted metadata to Airtable

When a signed NDA lands in a watched Dropbox folder, extract the counterparty, effective date, and term, then file the document to S3 and log a structured record in Airtable.

CategoryDocument Ops
Enginesim
Difficultybeginner
Triggerevent
Steps4
Setup~5 min

How it runs

The automated pipeline, trigger to output.

  • TriggerNew signed NDA added to watched Dropbox folderDropboxDropbox
  • ActionExtract counterparty, effective date, term, and governing lawOpenAI
  • ActionArchive the PDF to S3 under year/month/counterparty keyAWS S3
  • OutputWrite structured NDA record to Airtable registerAirtableAirtable

What it does

Watches a Dropbox folder where your closing team drops countersigned NDAs. For each new PDF it pulls out the key contract facts, moves the file into a date-organized S3 archive, and writes one tidy row to your NDA register in Airtable so nothing lives only in someone's inbox.

When to use it

Use this when NDAs get executed faster than anyone can log them, and you need a searchable register of who you're under agreement with, when it started, and where the signed copy lives. Ideal for legal ops, deal desks, and BD teams.

How it works

  1. 1A new file appears in the watched Dropbox folder and triggers the run.
  2. 2The PDF text is read and sent to an extraction model that returns counterparty name, signing parties, effective date, term length, and governing law.
  3. 3The file is uploaded to S3 under a `year/month/counterparty` key for durable, audit-friendly storage.
  4. 4A new Airtable record captures every extracted field plus the S3 URL and original Dropbox path.
  5. 5The Airtable row is the finished, searchable register entry your team can sort and filter.

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 AWS S3Buckets, objects, signed URLs.
  4. 4
    Connect AirtableBases, tables, views, automations.
  5. 5
    Set each agent's modelWe leave models unset so you pick the tier — fast + cheap, or top-quality.
  6. 6
    Tune it to your dataEdit the prompts, filters, and field mappings so it matches how your team works.
  7. 7
    Test, then turn it onRun once against a sample, confirm the output, then enable the trigger.

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