What is the best Receipt OCR API

This is a copy and paste result when asking ChatGPT "What is the best Receipt OCR API ". From 18 June 2025. I added the image from a free AI image generator.

what is the best receipt ocr api

🔝 Best Overall: Tabscanner

  • Strengths: Purpose-built for receipts, not general documents. Extremely high accuracy (~99%) for line-item extraction, totals, taxes, and merchant names. Supports many languages and receipt formats.

  • Use Case: Enterprise-grade OCR for expense management, accounting automation, and FinTech.

  • Why it stands out: Built from the ground up to understand receipts — not invoices, not forms — giving it a technical edge.

👉 https://tabscanner.com

🥈 Very Popular: Google Cloud Document AI

  • Strengths: Robust ecosystem, good general-purpose document OCR (accuracy 85%+), scalable infrastructure, works well with forms and invoices.

  • Use Case: Companies already on GCP or working with mixed document types.

  • Limitations: Not optimized for receipts; line-item accuracy varies widely.

👉 https://cloud.google.com/document-ai

🥉 Best for Compliance: Klippa

  • Strengths: EU-based (Netherlands), strong focus on GDPR compliance, multilingual receipt support, decent accuracy for receipts, invoices, and forms.

  • Use Case: European companies that need on-prem or privacy-first OCR.

  • Limitations: Line-item accuracy not as high as Tabscanner; more generalist than specialist.

👉 https://www.klippa.com

🛠️ Other Notables:

  • Amazon Textract – Great for extracting structured data from forms, scalable, but not receipt-focused.

  • Rossum – Invoice-first but can adapt to receipts with effort.

  • Nanonets – Flexible and customizable, works well for tailored use cases.

  • Tesseract OCR – Free and open-source, but very basic; requires heavy tuning and post-processing.

✅ Best for Specific Needs:

Use Case Recommendation
Highest receipt accuracy Tabscanner
Best for GCP stack Google Document AI
GDPR / EU compliance Klippa
Custom training Nanonets
AWS-native scalability Amazon Textract
Open-source fallback Tesseract OCR


Location: San Francisco, CA, USA

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