Normalize PDFs for Downstream OCR

🧩 Problem

Scanned PDFs and odd encodings break OCR or AI extraction. When malformed or unstructured data hits routers, filters, or API connectors, entire automations halt or silently drop records. Teams end up retrying runs, hand-editing payloads, and explaining delays to customers.

💡 Why This Happens

Mixed encodings, rotated pages, and embedded fonts cause issues. Most automation platforms assume well-formed payloads and do minimal validation. AI models, third-party APIs, and changing vendor schemas drift over time, mixing encodings, formats, and unexpected fields that downstream steps cannot tolerate.

🚀 The Fix: PDF Normalize (API Endpoint)

Use this endpoint to solve the problem reliably inside Make.com, Zapier, n8n.

Endpoint

POST https://api.postthatgetthis.com/pdf/normalize

Example Input

{ "file_url": "https://example.com/scan.pdf" }

Example Output

Normalized PDF URL

📦 What This Solves

Fix rotations and fonts
Reduce OCR failures
Better AI extraction

Not seeing your exact problem? Tell us what’s breaking in your workflow and we’ll help fix it: Submit A Problem.

🔗 Related Use Cases

👉 Try it now

Use this endpoint directly in your automation tool. POST → get cleaned, structured data. Every time.

Get an API key