We’re excited to introduce PdfParse - a novel approach to document data extraction that transforms unstructured PDFs into robust, normalized databases. Unlike traditional OCR tools that dump raw text or basic JSON, PdfParse leverages AI-powered extraction with automatic data normalization to create structured, queryable databases from your documents. And the best part? It’s incredibly cheap to use, with a free tier for evaluation and pay-per-page pricing that won’t break the bank.
Whether you’re processing invoices, receipts, contracts, or custom forms, PdfParse handles the complexity of nested data relationships, table extraction, and schema validation - delivering production-ready SQLite databases you can download and integrate immediately.
Features
Structured User Generated Schemas
With PdfParse, you define custom structured schemas tailored to your specific document types. Need to extract invoice data from PDFs? Create a schema that maps your invoice fields - from customer information to line items - and PdfParse handles the rest. Our structured schema builder lets you:
- Define custom tables with typed fields (text, numbers, dates, booleans)
- Set validation rules and constraints
- Create reusable templates for common document types
- Support complex data types and nested relationships
Simply design your schema once, and extract consistent, validated data from every PDF you process. No more wrestling with inconsistent JSON formats or manual data cleaning.
Nested and Hierarchical Table Extraction
PdfParse excels at understanding complex document structures with nested relationships. Here’s how our extraction pipeline works:
┌─────────────────────────────────────────────────────┐
│ Schema Definition │
│ │
│ ┌──────────────┐ ┌─────────────────┐ │
│ │ Invoice │────┬───→│ Customer │ │
│ │ │ │ │ │ │
│ │ - number │ │ │ - name │ │
│ │ - date │ │ │ - address │ │
│ │ - total │ │ │ - email │ │
│ └──────────────┘ │ └─────────────────┘ │
│ │ │ │
│ │ │ ┌─────────────────┐ │
│ └────────────┴───→│ Invoice_Items │ │
│ │ │ │
│ │ - description │ │
│ │ - quantity │ │
│ │ - price │ │
│ └─────────────────┘ │
└─────────────────────────────────────────────────────┘Once you’ve created your schema with parent-child table relationships (like invoice → customer and invoice → invoice_items), the extraction process is simple:
- Upload your PDF files to your project
- Click the “Process Files” button
- PdfParse extracts data according to your schema, populating parent and child tables
- Any extraction issues are saved as errors for later review and retry
Here’s what happens under the hood:
┌──────────────────────────┐
│ Invoice PDF │
│ │
│ INVOICE #12345 │
│ Date: 2025-01-15 │
│ Customer: Acme Corp │
│ │
│ Items: │
│ - Widget A $100 │
│ - Widget B $200 │
│ Total: $300 │
└──────────────────────────┘
│
▼
┌───────────────┐
│ AI Pipeline │
│ (Extraction) │
└───────────────┘
│
▼
┌─────────────────────────────────────┐
│ SQLite Database │
│ │
│ invoices: │
│ ├─ id: 1 │
│ ├─ number: "12345" │
│ ├─ date: "2025-01-15" │
│ └─ total: 300.00 │
│ │
│ customers: │
│ ├─ id: 1 │
│ ├─ invoice_id: 1 (FK) │
│ └─ name: "Acme Corp" │
│ │
│ invoice_items: │
│ ├─ id: 1, invoice_id: 1 │
│ │ description: "Widget A" │
│ │ price: 100.00 │
│ └─ id: 2, invoice_id: 1 │
│ description: "Widget B" │
│ price: 200.00 │
└─────────────────────────────────────┘SQLite as a Single Source of Truth
We chose SQLite over basic JSON for a compelling reason: it’s robust, portable, and fast - making it the backbone of most LLM agents and modern data pipelines. Here’s why SQLite makes sense:
- Robust: ACID-compliant transactions, data integrity, and reliability
- Portable: A single file containing your entire structured database
- Fast: Efficient querying, indexing, and aggregations without external dependencies
- Universal: Supported by virtually every programming language and framework
- Downloadable: Export your complete database as a
.sqlitefile for offline use, backups, or integration with existing systems
Instead of parsing nested JSON structures, you get a real relational database with foreign keys, indexes, and SQL querying capabilities. Use it directly in your applications, connect it to BI tools, or feed it to AI agents for natural language queries.
Coming soon: API access and webhook integrations for real-time data synchronization with your systems.
Human Readable Errors
Extraction isn’t always perfect, especially with complex or low-quality documents. That’s why PdfParse provides human-readable error messages with a built-in review interface:
- View detailed error messages for each failed extraction field
- See exactly which document and field encountered issues
- Review errors in context with the original PDF
- Trigger individual or batch retries for failed extractions
- Track error resolution progress across your projects
No more digging through logs or debugging cryptic error codes. PdfParse surfaces extraction issues in a clear, actionable format so you can quickly identify patterns, fix schema definitions, or manually correct edge cases.
SQL Table Based Navigation
Once your documents are processed, navigate your extracted data like a SQL explorer. PdfParse provides an intuitive table-based interface where you can:
- Browse all tables in your database with familiar spreadsheet-like views
- Search and filter data across any field
- View parent-child relationships and navigate between linked records
- Execute custom SQL queries for advanced analysis
- Export individual tables or entire databases as CSV, JSON, or SQLite files
It’s the power of a full database client, built directly into your extraction workflow. No need to download databases and open external tools - explore your data immediately after extraction.
Pricing
We believe document extraction should be affordable and accessible to everyone. That’s why we’ve designed competitive pricing that scales with your needs, without hidden fees or surprise charges.
Free Tier
Try PdfParse risk-free with our free evaluation tier. Test the product with real documents before committing to a paid plan:
┌──────────────┬─────────────────┬──────────────┐
│ Plan │ Pages/Month │ Price/Month │
├──────────────┼─────────────────┼──────────────┤
│ Free │ 20 │ $0.00 │
│ Basic │ 800 │ $29.99 │
│ Pro │ 3,000 │ $79.99 │
│ Enterprise │ 10,000 │ $129.99 │
└──────────────┴─────────────────┴──────────────┘Transparent, Token-Based Pricing
- Tokens deducted per page, not per document - a 10-page PDF uses 10 tokens
- No charges for failed extractions - you only consume tokens for successful page processing
- Fixed monthly allowance - each plan includes a set number of pages per month
- Cancel anytime with no penalties or long-term commitments
Our pricing is designed to be cheap compared to traditional document processing services that charge per document or require expensive enterprise contracts. With PdfParse, you get production-ready extraction at a fraction of the cost.
Get Started Today
Ready to transform your document workflow? Sign up for a free account at pdfparse.net and start extracting structured data in minutes.
Questions? Reach out to us at support@pdfparse.net - we’d love to hear about your use case.