Extract Text from PDF
Infoveave Data Automation — Document Parsing
Digital PDF in. Extracted, structured data out. No copy-paste required.
Organizations receive high volumes of PDFs — invoices, purchase orders, bank statements, regulatory filings — that contain structured data locked inside a document format. Manually copying fields to a spreadsheet is slow, error-prone, and doesn't scale. Extract Text from PDF reads the text content of machine-readable PDFs and uses markers, column maps, and regex patterns to pull out exactly the fields you need — converting document data into a table ready for analytics and database loading.
What Extract Text from PDF does
Extract structured field data from machine-readable PDF documents using segment markers, column mapping, and regex patterns inside your Infoveave workflow. No manual copy-paste — automated ingestion of invoices, contracts, reports, and statements.
When to use Extract Text from PDF
- You receive machine-readable PDFs (generated by software, not scanned) with structured data fields to extract
- Your workflow ingests invoices, bank statements, purchase orders, or regulatory filings in PDF format
- You need to extract specific fields from PDF documents at scale without manual data entry
- You want to define extraction rules once and apply them to every PDF that matches the same template
When to avoid it
- Your PDFs are scanned images or contain image-based text — use Extract OCR from PDF instead, which applies optical character recognition
- You only need to split or rearrange PDF pages — use Split PDF
- Your PDFs contain barcode elements you need to decode — add Read Barcode to your pipeline
Where it fits in your Infoveave automation
Extract Text from PDF is one step inside a multi-step Infoveave workflow. Chain it with other activities — no code, no manual hand-offs.
Build this workflow visually in Infoveave Data Automation — drag, connect, and schedule with no infrastructure setup.
How teams use Extract Text from PDF
Real scenarios where this transformation saves hours of manual work.
Invoice Processing Automation
Supplier invoices arrive as standardized PDF templates. Extract Text from PDF uses segment markers to identify each invoice section and a column map to extract vendor name, invoice number, line items, and totals — populating the AP system without manual data entry.
Lab Report Data Extraction
Clinical lab systems generate PDF reports with structured result tables. The extraction workflow uses markers to isolate the results section and regex patterns to capture test codes, values, and reference ranges, loading them into the patient data platform.
Contract Term Extraction
Standard contract templates generated from the legal management system include consistent section markers. Extract Text from PDF captures key terms — effective date, termination clauses, renewal options — from thousands of contracts for the automated contract analytics dashboard.
See Extract Text from PDF in action
Input data (left) is transformed using the configuration below. The output table (right) is ready for dashboards or downstream steps.
Start: '--- INVOICE START ---', End: '--- INVOICE END ---'Invoice Number → InvoiceNo, Vendor → VendorName, Total → TotalAmountInvoice No: (INV-\d+), Total Amount: \$([\d,\.]+)Input Data
| PDF content snippet |
|---|
| --- INVOICE START --- |
| Invoice No: INV-20260411 |
| Vendor: Acme Supplies Ltd |
| Total Amount: $4,220.00 |
| --- INVOICE END --- |
Output Data
| InvoiceNo | VendorName | TotalAmount |
|---|---|---|
| INV-20260411 | Acme Supplies Ltd | 4220.00 |
Configuration
Key fields to configure in the Infoveave workflow builder. Full reference available in the documentation.
Markers
Text strings that mark the start and end of the section to extract within each PDF. The activity only processes content between these markers, allowing you to scope extraction to the relevant document section even when the PDF contains other content.
Column Map
Mapping of document field labels to output column names. Specify each document field (as it appears in the PDF text) and the target column name in the output table.
Regex Extractors
Regular expression patterns that capture specific field values from the text. Use named capture groups to extract values such as invoice numbers, dates, amounts, or codes from each document.
Frequently asked questions
Everything you need to know about Extract Text from PDF in Infoveave.
Also in Document Parsing — and what runs before & after
Transformations in the same family as Extract Text from PDF, often chained together in the same Infoveave workflow.
Part of Infoveave Data Automation
80+ transformations. Zero manual steps.
Extract Text from PDF is one of over 80 transformation activities available inside Infoveave workflows. Chain transformations together — no code, no exports, no waiting for IT.
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