Automate Invoice Data Extraction from Google Drive to Airtable using Nanonets OCR & Command-R

How it works

This template creates a fully automated "hands-off" pipeline for processing financial documents. It's perfect for small businesses, freelancers, or operations teams who want to stop manually entering invoice and receipt data.

When you drop a new image/multiple images file into a specific Google Drive folder, this workflow automatically:

1. Triggers and downloads the new file.
2. Performs OCR on the file using a local AI model (Nanonets-OCR-s) to extract all the raw text.
3. Cleans & Structures the raw text using a second local AI model (command-r7b). This step turns messy text into a clean, predictable JSON object.
4. Saves the structured data (like InvoiceNumber, TotalAmount, IssueDate, etc.) to a new record in your Airtable base.
5. Moves the original file to a "Done" or "Failed" folder to keep your inbox clean and organized.

Requirements

• Google Drive Account: For triggering the workflow and storing files.
• Airtable Account: To store the final, structured data.
• Ollama (Local AI): This template is designed to run locally for free. You must have Ollama running and pull two models from your terminal:
  • ollama pull benhaotang/Nanonets-OCR-s:F16
  • ollama pull command-r7b:7b-12-2024-q8_0

How to set up

Setup should take about 10-15 minutes. The workflow contains 7 sticky notes that will guide you step-by-step.

1. Airtable: Use the link in the main sticky note ([1]) to duplicate the Airtable base to your own account.
2. Ollama: Make sure you have pulled the two required models listed above.
3. Credentials: You will need to add three credentials in n8n:
   • Your Google Drive (OAuth2) credentials.
   • Your Airtable (Personal Access Token) credentials.
   • Your Ollama credentials. (To do this, create an "OpenAI API" credential, set the Base URL to your local server (e.g., http://localhost:11434/v1), and use ollama as the API Key).
4. Follow the Notes: Click through the workflow and follow the numbered sticky notes ([1] to [6]) to connect your credentials and select your folders for each node.

How to customize the workflow

• Use Cloud AI: This template is flexible! You can easily swap the local Ollama models for a cloud provider (like OpenAI's GPT-4o or Anthropic's Claude 3). Just change the credentials and model name in the two AI nodes (OpenAI Chat Model and Data Cleaner).
• Add More Fields: To extract more data (e.g., SupplierVATNumber), simply add the new field to the prompt in the Data Cleaner node and map it in the AirTable - Create a record1 node.