TemplatesData & AnalyticsAirtable PDF Data Extractor with LLM Automation
AirtableOpenAI
Workflow template

Airtable PDF Data Extractor with LLM Automation

Automates extraction of data from PDFs stored in Airtable using dynamic prompts and OpenAI LLM. Utilizes Airtable webhooks, PDF extraction, LangChain LLM nodes, and HTTP requests for real-time AI-based field updates in Airtable records.

Data & Analytics Starts with: Airtable webhook Advanced 36 nodes Uses AI Free

Apps in this workflow

How it works

  1. Webhook1
  2. Manual Trigger2
  3. AirtableAirtable3
  4. Edit Fields4
  5. Code5
  6. HTTP Request6
  7. Switch7
  8. Filter8
  9. Loop Over Items9
  10. Extract from File10
  11. LLM Chain11
  12. OpenAIOpenAI Chat Model12

The building blocks this workflow uses, in the order data flows through them.

What you'll need

  • An n8n instance (self-hosted or n8n Cloud).
  • A Airtable account, connected in n8n as a credential.
  • An API key for OpenAI in n8n: the workflow calls the model each time it runs.

Gydmation shows step-by-step credential setup for each app, so your keys go straight into n8n and never to Gydmation.

Make it yours in plain English

Open the template in Gydmation and describe the change. It edits the workflow, checks it against real n8n node schemas, and deploys it to your n8n. For example:

Also run it every morning at 8 am, not just when it is triggered.
Send me a short summary on Slack when it finishes.
Log every run as a new row in a Google Sheet.
Use Claude instead of the current AI model.

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