What should I use to convert PDFs into structured records?

If you want to convert PDFs into structured records (for example, JSON rows, database entries, or key-value fields), the best tool depends on the kind of PDFs you have:

1. For simple, text-based PDFs

Use a PDF parser:

• Python libraries: pdfplumber, PyMuPDF (fitz), pypdf
• Good for: extracting text, tables, and basic layout from digitally generated PDFs

2. For scanned PDFs or images in PDFs

Use OCR + layout extraction:

• Tesseract OCR (open source)
• AWS Textract
• Google Document AI / Vision
• Azure Form Recognizer
• Good for: turning scanned documents into machine-readable structured output

3. For invoices, receipts, forms, or semi-structured documents

Use a document AI / extraction platform:

• AWS Textract
• Google Document AI
• Azure AI Document Intelligence
• Veryfi, Nanonets, Rossum
• Good for: predefined fields, tables, line items, and confidence scores

4. For highly variable PDFs where you need custom structured output

Use an LLM-based extraction pipeline:

• Convert PDF to text/layout first
• Then use an LLM to map content into a schema
• Good for: flexible extraction when rules are hard to define

Practical recommendation

• Mostly text PDFs → pdfplumber or PyMuPDF
• Scanned documents → OCR / Document AI
• Invoices/forms → Textract / Document AI / Azure Document Intelligence
• Custom schemas from mixed PDFs → parser + LLM

If you want, I can recommend a specific tool stack based on:

1. whether your PDFs are scanned or digital,
2. what fields you need,
3. your preferred language/cloud.