Extract Text by Expression - RegEx for Make

PDF4me Extract Text By Expression module delivers automated pattern-based text extraction from PDF documents within Make scenarios using regular expressions and search patterns. This intelligent data extraction service finds and retrieves invoice numbers, dates, amounts, email addresses, phone numbers, and custom text patterns—enabling structured data extraction, automated parsing, field identification, and intelligent document processing workflows across cloud storage platforms and business applications.

Authenticating Your API Request

To access the PDF4me Web API through Make, every request must include proper authentication credentials. Authentication ensures secure communication and validates your identity as an authorized user, enabling seamless integration between your Make scenarios and PDF4me's powerful text extraction services.

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Key Features

• Regex Support: Use regular expressions for powerful pattern matching
• Multi-Match Extraction: Retrieve all matching text instances
• Page-Specific: Target specific pages or all pages
• Structured Output: Returns matches as text array
• Data Mining: Extract specific data patterns from unstructured PDFs

Parameters

Complete list of parameters for the Extract Text By Expression module. Configure these parameters to control text extraction.

Important: Parameters marked with an asterisk (***) are required and must be provided for the module to function correctly.

Parameter	Type	Description	Example
PDF File Name***	String	Source PDF Filename • Specify filename with .pdf extension • Map from previous module output • PDF containing text to extract • Supports dynamic naming	invoice.pdf
PDF File***	Buffer	PDF File Content • Map PDF file buffer from previous module • Source from Dropbox, Google Drive, email • Binary PDF with text content • Invoice, form, or document with data	[PDF Buffer]
Expression***	String	Search Pattern/Regex • Regular expression or search pattern • Extract specific text patterns • Examples: invoice numbers, dates, emails • Can use simple text or complex regex	INV-[0-9]{4}
Page***	String	Target Page Selection • Comma-separated page indices (0-based) • Supports ranges with hyphen • Empty processes all pages • String format required	0-

Output

The PDF4me Extract Text By Expression module returns comprehensive match data for seamless Make scenario integration:

Table

Table View

Response data in a structured table format:

Parameter	Type	Description
Text List	Array of Strings	All text matches found using expression

JSON

JSON Response Format

The raw JSON response from the module:

{
  "Text List": [
    "INV-2024-0001",
    "INV-2024-0045",
    "INV-2024-0123"
  ]
}

Scenario Integration

Make Scenario Usage

Use extracted text in subsequent modules:

• Database Lookup: Query database with extracted values
• Data Validation: Verify extracted data against records
• Iterator: Process each match individually
• Email Notification: Send alerts with extracted data
• Spreadsheet: Log extracted values in Google Sheets
• API Integration: Post extracted data to external systems

Scenario Examples

The PDF4me Extract Text By Expression module in Make provides comprehensive scenario templates for text extraction automation:

Invoice Extraction

Automated Invoice Number Extraction Scenario

Transform your invoice processing with automated number extraction:

Complete Scenario Steps:

1. Trigger: Watch Email for invoice PDFs
2. Get Invoice PDF: Extract PDF from email attachment
3. Extract Invoice Number: Use pattern "INV-[0-9]+" to find number
4. Extract Amount: Use pattern to find total amount
5. Extract Due Date: Find date pattern in document
6. Create Invoice Record: Insert data into accounting system
7. Archive Invoice: Store PDF with extracted metadata
8. Notify AP Team: Alert accounts payable of new invoice

Business Benefits:

• Processes 300+ invoices monthly automatically
• Eliminates manual invoice number entry
• Enables automated invoice tracking and routing
• Reduces invoice processing time by 85%

Create Scenario

Contact Extraction

Automated Contact Information Extraction Scenario

Streamline your CRM with automated contact data extraction:

Complete Scenario Steps:

1. Trigger: Business card or resume PDF received
2. Get Document PDF: Download PDF with contact info
3. Extract Email: Use email pattern regex
4. Extract Phone: Use phone number pattern
5. Extract Name: Find name patterns in document
6. Extract Company: Identify company name
7. Create Contact: Insert into CRM or Airtable
8. Email Confirmation: Send contact added notification

Business Benefits:

• Extracts 100+ contact records monthly automatically
• Eliminates manual contact information entry
• Maintains accurate CRM database
• Reduces contact data entry time from 5 minutes to 10 seconds

Create Scenario

PO Extraction

Automated Purchase Order Number Extraction Scenario

Optimize your procurement with automated PO number extraction:

Complete Scenario Steps:

1. Trigger: Purchase order confirmation PDF received
2. Get PO PDF: Download purchase order document
3. Extract PO Number: Use pattern "PO-[0-9]+" regex
4. Extract Vendor: Find vendor name pattern
5. Extract Line Items: Extract product codes and quantities
6. Update Inventory: Post PO data to inventory system
7. Create Receipt Record: Prepare receiving document
8. Archive PO: Store with extracted metadata

Business Benefits:

• Processes 150+ purchase orders monthly automatically
• Extracts key PO data without manual entry
• Enables automated inventory and procurement tracking
• Reduces PO processing time by 80%

Create Scenario

Compliance Data

Automated Compliance Document Data Extraction Scenario

Enhance your compliance with automated pattern-based extraction:

Complete Scenario Steps:

1. Trigger: Compliance report PDF submitted
2. Get Compliance PDF: Download regulatory document
3. Extract Case Numbers: Use pattern for case IDs
4. Extract Dates: Find submission and effective dates
5. Extract Reference Numbers: Retrieve regulatory references
6. Store in Database: Import extracted data to compliance DB
7. Generate Index: Create searchable compliance index
8. Archive Document: Store with extracted metadata

Business Benefits:

• Processes 50+ compliance documents monthly
• Extracts key compliance identifiers automatically
• Enables compliance document search and tracking
• Reduces compliance data entry by 90%

Create Scenario

Industry Use Cases & Applications

Finance & Accounting

• Invoice Data: Extract invoice numbers and amounts
• PO Processing: Retrieve purchase order numbers
• Account Numbers: Extract bank account information
• Transaction IDs: Find payment reference numbers

Legal & Compliance

• Case Numbers: Extract legal case identifiers
• Contract Terms: Find specific contract clauses
• Regulatory IDs: Retrieve compliance reference numbers
• Date Extraction: Find effective and expiration dates

Data Processing & Analysis

• Pattern Mining: Extract specific data patterns
• Field Extraction: Retrieve structured field data
• Data Validation: Extract values for validation
• Research Data: Find research identifiers and codes

Business Operations

• Order Numbers: Extract customer order IDs
• Tracking Numbers: Retrieve shipment tracking codes
• Reference Numbers: Find document reference identifiers
• Contact Information: Extract emails and phone numbers

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