Payroll PDF Processing and Approval Automation

Step 1: Set Up Google Drive Folders

No nodes needed – just create two folders in your Drive:

• Source: "Payroll - For Signature"
• Destination: "Payroll - Approved"

Success Looks Like: Two folders ready for workflow input/ouput.

Step 2: Trigger on New Payroll File

Node: Google Drive → Changes Involving a Specific Folder

Settings:

• Folder to Watch: "Payroll - For Signature"
• Watch For: File Created

Success Looks Like: Workflow starts when a new PDF is added.

Step 3: Download Payroll File

Node: Google Drive → File

Settings:

• Operation: Download
• File ID: {{ $json.id }}

Success Looks Like: PDF file downloaded as binary data.

Note: This step is especially important if your Google Drive and sharing settings are restricted, helping ensure secure access to sensitive files like payroll.

Step 4: Upload to PDF.co

Node: PDF.co API → Upload File

Settings:

• Upload Method: Standard Upload
• Binary File: True
• Input Binary Field: data
• Name: file.pdf

Success Looks Like:

{
  "url": "https://pdf-co-temp-files.s3.amazonaws.com/...",
  "name": "file.pdf"
}

Step 5: Remove PDF Password Protection

Node: PDF.co API → PDF Security

Settings:

• Url: {{ $json.url }}
• Operation Mode: Remove Security
• File Password: (Your file’s password)

Success Looks Like: Payroll file is unlocked and ready.

Step 6: Split PDF into Individual Payslips

Node: PDF.co API → Split PDF

Settings:

• Url: {{ $json.url }}
• Split By: Page Numbers
• Pages: * (splits all pages; see API Docs for more options)
• Inline: True

Success Looks Like:

{
  "body": [
    "https://pdf-co.../page1.pdf",
    "https://pdf-co.../page2.pdf",
    "https://pdf-co.../page3.pdf"
  ]
}

Step 7: Process Each Payslip

Node: Split Out

Settings:

• Field to Split Out: body
• Include: No Other Fields

Success Looks Like: Each payslip URL processed individually.

Step 8: Extract Employee Names

Node: PDF.co API → Search in PDF

Settings:

• PDF URL: {{ $json.body }}
• Search String: (?<=Employee Name:\s)([A-Z][a-z]+\s[A-Z][a-z]+)(?=\s)
• Use Regex: True
• Pages: 0-
• Inline: True

Success Looks Like:

{
  "url": "https://pdf-co.../results.json..."
}

Step 9: Download Extracted Names

Node: HTTP Request

Settings:

• Method: GET
• URL: {{ $json.url }}

Success Looks Like: Employee name data retrieved successfully.

Step 10: Add Signature and Rename PDF

Node: PDF.co API → Add Text/Images to PDF

Settings:

• URL: {{ $('Split Out').item.json.body }}
• Images:
  • Image Url: https://image_link
  • X-Coordinate: 49.58
  • Y-Coordinate: 349.97
  • Width: 234.68
  • Height: 106.75
• Advanced Options:
  • File Name: {{ $json.text }}.pdf

Signature Setup:

• Use a PNG or JPG of your signature.
• Host it on cloud storage (e.g., Google Drive).
• Replace Image URL with the hosted file link.
• Tip: Use the PDF Inspector tool to fine-tune placement. Import the sample project to get started.

Success Looks Like:

{
  "url": "https://pdf-co.../John_Smith.pdf...",
  "name": "John_Smith.pdf"
}

Step 11: Download Signed PDF

Node: HTTP Request

Settings:

• Method: GET
• URL: {{ $json.url }}

Success Looks Like: Signed PDF downloaded as binary data.

Step 12: Upload to Approved Folder

Node: Google Drive → Upload

Settings:

• Resource: File
• Input Data Field Name: data
• Parent Drive: My Drive
• Parent Folder: Payroll - Approved

Success Looks Like: Signed payslip stored in the "Payroll - Approved" folder.