🍲 Extract Data from Google Drive Documents with Make

🧰 Use Case

Automatically parse documents (PDFs, Word docs, images, email files, etc.) placed in a Google Drive folder. Extract structured data using Airparser without manual uploading — fully automated via Make.

🔍 Requirements

⚙️ What’s Being Built

• Trigger: New file appears in a specific Google Drive folder

• Intermediate Step: Download file content

• Action: Send file to Airparser for parsing

• Optional next steps: Save results, export, or route the data wherever needed

🪜 Recipe Steps

1. Create a new scenario in Make

• • Select Google Drive as the trigger module → “Watch Files in a Folder”.

  • Select Airparser as the action module → “Upload a Document for Parsing”.

2. Connect Google Drive

• • Add a new connection for Google Drive.

  • Important for Gmail/Googlemail users: you must set up a custom OAuth client in the Google Cloud Platform and supply client credentials. This is required to use Google Drive with restricted scopes via personal accounts. Learn more here.

3. Select the folder to monitor

• • Choose the Drive (e.g. My Drive) and select a folder (e.g. Airparser inbox) where you will drop your documents.

  • Optionally, set filters such as “file types to watch” and limit number of files per run.

4. Download the file

• • Add a Google Drive → Download a File action.

  • This ensures Make pulls in the actual document content so it can be handed off to Airparser.

5. Configure Airparser upload

• • Connect your Airparser account in Make.

  • Select the Airparser inbox where parsed documents should be sent (e.g. “Invoices”).

  • Map the file content obtained from Google Drive into the Airparser module.

  • Optionally include metadata via a custom payload (e.g. project name, client ID, tags).

6. Test the workflow

• • In Make, click Run once to run a test execution.

  • Upload a sample document into your monitored Google Drive folder.

  • Observe Make detecting the file, downloading it, and submitting it to Airparser.

7. Check parsing result

• • Log into Airparser → open the inbox.

  • Wait for parsing status to move from Parsing → Parsed.

  • Verify extracted fields match what you defined in your schema.

8. (Optional) Post-processing

• • Export the parsed data (JSON, CSV, Excel).

  • Send it onward to Google Sheets, other apps via Make, a webhook, or your internal tools.

  • Add notifications or automated routing (e.g. send to Slack, your accounting system, etc.).

📋 Expected Result

Once successfully set up:

• Any document you drop into your Google Drive folder is automatically picked up.

• Airparser will extract structured data fields (invoice number, date, line items, total, sender, etc.) based on your schema.

• Parsed data is available in the format you choose (JSON, Excel, CSV, etc.) or forwarded to downstream tools.

• No manual uploading or copy-pasting required.

⚠️ Notes & Troubleshooting

• Gmail/Googlemail accounts require extra setup: without a custom OAuth client and client credentials, you may see errors or be unable to connect Google Drive in Make.

• Make triggers may have limits on polling frequency or file limits per run — plan accordingly.

• For certain file types (e.g. scanned images or email attachments), ensure your Airparser schema supports those formats (OCR, email parsing, etc.).

• Test with varied sample documents to ensure schema covers edge cases (multiple line items, different layouts, optional fields, etc.).

✅ Tips for Best Practice

• Use consistent naming for your Google Drive folder to avoid confusion.

• Include identifying metadata in the custom payload (if multiple workflows share the same inbox).

• Monitor error logs in Make and Airparser to catch parsing failures.

• Schedule scenario execution frequency in Make as needed (every few minutes, hourly, etc.).