Extract Data from PDF to JSON (API + Example)
Send any PDF to Parselyze and receive structured JSON with the fields you define, from invoices and contracts to scanned forms and financial reports. No scripting required.
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Best fit for
Engineering teams building document pipelines, finance automation, data ingestion workflows, and any system that needs data out of PDFs.
Any PDF type
Digital PDFs, scanned documents, and image files all processed through the same API endpoint.
Tables included
Extracts table rows and nested line items alongside scalar fields in the same JSON response.
No maintenance
Define your fields once. The AI handles layout variation, different fonts, and formatting changes automatically.
What is PDF data extraction?
PDF data extraction is the automated process of reading a PDF document and pulling out specific fields (such as dates, amounts, names, and table rows) into a structured format like JSON. Unlike copy-paste or basic OCR, PDF data extraction maps each value to a named key you define once, so the output is immediately usable in your application.
Parselyze provides a PDF data extraction API that handles digital PDFs, scanned PDFs with built-in OCR, multi-page documents, and image inputs. Define your fields in the Template Builder, submit the document via API, and receive structured JSON in seconds.
How to extract data from a PDF
Rather than dealing with raw text, you receive structured fields ready to be used in your application. This allows for easy integration of PDF data extraction into data pipelines, internal systems, and automated workflows.
Upload a PDF
Send your PDF document to Parselyze via our API. You can upload any PDF, whether it's a digital file or a scanned document.
Fields are detected
Parselyze detects and extracts relevant fields, tables, and data from your documents, regardless of their layout or format.
Receive structured JSON
Get the result of PDF to JSON conversion, ready to be used in your application or data pipeline.
PDF to JSON extraction example
Send a PDF to Parselyze via API and receive structured JSON in seconds, ready for any downstream system.
{ "invoice_number": "FCT-000342", "invoice_date": "2024-05-28", "vendor_name": "ACME Corporation", "vendor_address": "123 Innovation St, Example City", "bill_to": "John Example", "bill_to_address": "456 Demo Ave, Sampletown", "currency": "USD", "total_amount": 1500.00, "line_items": [ { "description": "Consulting services", "qty": 8, "unit_price": 125.00, "total": 1000.00 }, { "description": "Design mockups", "qty": 1, "unit_price": 500.00, "total": 500.00 } ] }
Supported PDF Types
Parselyze supports every PDF types, such as invoices, receipts, financial reports, contracts, forms, scanned documents, and more.
Invoices
Extract totals, dates, line items, and more from scanned invoices.
Receipts
Parse merchant names, amounts, and dates from receipts for expense tracking.
Contracts
Extract parties, dates, and clauses from contracts and agreements.
Financial reports
Convert financial statements and reports into structured data for analysis.
Forms and surveys
Parse filled-out forms and surveys to extract responses and metadata.
Scanned documents
Convert scanned PDFs of any type into structured JSON for downstream processing.
Typical Workflows
Parselyze supports a variety of workflows, such as invoice processing, receipt data extraction, contract data ingestion, and document ingestion pipelines.
Invoice processing automation
Convert scanned invoices into structured JSON to automatically import totals, dates, and line items into accounting systems.
Receipt data extraction
Extract merchant names, amounts, and dates from receipts to automate expense tracking and reimbursements.
Contract data ingestion
Parse contracts and agreements to extract key information like parties, dates, and clauses for internal systems.
Document ingestion pipelines
Convert large volumes of PDFs and scanned documents into structured JSON to feed data warehouses or automation workflows.
Add PDF extraction to any application
Install the SDK or call the REST API directly. For large volumes, use the async job queue and receive results via webhook as each document completes.
Ready to integrate?
SDK examples, REST API reference, webhook handler, and cURL samples are all available in the developer docs.
Frequently asked questions
Everything you need to know about PDF data extraction.
What does PDF data extraction mean?
PDF data extraction is the process of automatically pulling structured fields, tables, and values from PDF documents without manual copy-paste. The result is clean JSON ready for databases, APIs, or automation workflows.
What PDF formats are supported?
Parselyze supports native digital PDFs, scanned PDFs (with built-in OCR), multi-page PDFs, and PDF images. JPEG, PNG, WEBP, TIFF, and BMP image inputs are also accepted.
How do I extract data from a PDF?
Create a template in the Parselyze dashboard defining the fields you want, then submit the PDF via REST API or Node.js SDK. You receive a structured JSON response in seconds. For bulk volumes, use the async job queue with webhook delivery.
Can Parselyze extract tables from PDFs?
Yes. Parselyze extracts table rows and nested line items alongside scalar fields in the same JSON response — no separate pipeline required.
How is PDF data extraction different from OCR?
OCR converts document images to raw text. PDF data extraction goes further: it maps that text into named, typed fields defined by your template. The output is structured JSON, not a block of text.
Do I need to train a model for each PDF layout?
No. You define the fields once in the Template Builder. The AI handles layout variation, different fonts, and formatting differences automatically across document variants.
Start extracting data from PDFs today
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