📄 PDF to JSON Parser

🚀 Convert PDFs into structured JSON in seconds. Upload any PDF and get clean, queryable fields. Optional field selection and custom prompts. No coding, no manual data entry.

Convert PDF documents into clean, structured JSON without writing custom parsers per document type. Upload one or more PDFs, optionally tell the actor which fields to extract, and the AI processes every page and returns one record per document with the extracted fields plus full page text. Built for invoice automation, contract review, research-paper indexing, regulatory filings, and any workflow that turns scanned or born-digital PDFs into queryable data.

The output is a structured record per file: a back-reference to the source PDF, the document name, the number of pages, a topic summary, a timestamp, and the extracted fields under fetchedData. Hand the dataset off to your database, BI tool, or AI pipeline. Every run is processed live with no caching of input PDFs.

👥 Built for	🎯 Primary use cases
Finance and AP teams	Auto-extract invoice fields into accounting systems
Legal and contract ops	Pull key terms, dates, parties from contracts
Research and academia	Index research papers for full-text search
Compliance and regulatory	Convert filings into queryable records
HR and recruiting	Parse resumes into structured candidate profiles
Data and engineering teams	Replace bespoke PDF parsers across products

📋 What the PDF to JSON Parser does

• 📄 Multi-PDF input. Upload one or more PDFs via file upload or URL.
• 🧠 Smart extraction. Optionally specify the exact fields you want, or let the AI pick the important ones.
• ✏️ Custom prompts. Pass a system prompt to bias extraction toward your domain (legal, medical, financial, etc.).
• 📊 Page-aware. All pages of every PDF are processed before parsing, so nothing is lost.
• 🆔 Back-reference. Every record links back to the original PDF in the dataset.
• ⏱️ Timestamp. Every record carries a timestamp so you can rebuild a timeline.

The actor processes uploads in the order you provide them. Records stream into the dataset as parsing completes, so you can start consuming results before the run is fully finished. Ideal for workflows that need clean structured data from inconsistent PDF layouts.

💡 Why it matters: PDFs are the universal data format that nobody wants to parse. Bespoke parsers break with every layout change. AI-driven extraction adapts to layout variation without code changes, so finance, legal, and research teams can get from "PDF inbox" to "structured database" in minutes.

📊 Data fields

Each record includes: documentName, fetchedData, numberOfPages, timestamp, topic. All 5 field names come from a real production run, so what you see here is what lands in your dataset.

🚀 How to use

1. 📝 Sign up. Create a free account with $5 credit (takes 2 minutes).
2. 🌐 Open the Actor. Go to the PDF to JSON Parser page on the Apify Store.
3. 🎯 Upload your PDFs. Drop one or more PDFs and (optionally) list the fields you need.
4. 🚀 Run it. Click Start and let the Actor extract structured data.
5. 📥 Download. Grab your results in the Dataset tab as CSV, Excel, JSON, or XML.

⏱️ Total time from signup to first parsed PDF: 3-5 minutes for a short document.

🔗 Recommended Actors

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• 🌐 Website Content Crawler - Crawl entire sites and export structured content

💡 Pro Tip: browse the complete ParseForge collection for more reference-data scrapers.

⚠️ Disclaimer. This Actor is an independent tool. The actor processes only PDFs you supply by URL and is intended for legitimate document automation workflows. Users are responsible for ensuring they hold the rights to parse the PDFs they submit and for compliance with copyright, privacy, and licensing laws in their jurisdiction.

🆘 Need Help?

If you hit a bug, have questions about setup, or need a scraper we haven't built yet, open our contact form or write to parseforge@protonmail.com. We also take on paid custom data projects.

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