Reimagined by iLoveOCR V4.0
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Pricing Plans

Recognize RAW and Create Mobi

Turn bulky RAW documents into pocket-sized Mobi assets. Process your private documents locally and take your entire library with you on your Kindle.

Supports 80+ Formats

DROP FILES HERE

Guest: Basic | 2MB Limit
Sign up to Unlock Batch & Pro Layouts
Release to Recognize
Language Auto-Detect Language

Select OCR Language

Multi-Language Support · 110+ Languages

Output Format Word (.docx) Basic · Text Only
Word (.docx) Basic · Text Only
Excel (.xlsx) Basic OCR · No Table Structure
Text File (.txt) Plain Text · High Compatibility
Pro Only AI Batch & Merge
Word (.docx) High-Fidelity Layout
Pro Ultra
Excel (.xlsx) Finance-Grade Alignment
Pro Ultra
PowerPoint (.pptx) Dynamic Slide Rebuild
Standard Pro Ultra
Epub / Mobi / Azw3 Kindle · Auto De-clutter
Basic Pro Ultra
Markdown (.md) Auto Title Detection
Standard Pro Ultra
Enterprise AI Engine
Searchable PDF (Dual-Layer) VLM Engine · Text Layer · GPU Priority
Ultra Ultra
PRO
AI Enhancement Layout Analysis

Optimize RAW Scans
for Kindle Mobi Reading

Convert your static RAW files into Mobi ebooks optimized for Amazon Kindle devices. Our engine ensures that text is reflowable and crystal clear, providing a native reading experience on your favorite e-reader.

User User User
1K+
4.9/5

Trusted by 1,081 Global Users

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Tailored
Kindle Layout Optimization

We analyze the typographic density of your RAW source to generate Mobi files that respect the Kindle legacy standard. By optimizing font embedding and image compression, iLoveOCR makes your digital books lightweight and easy to navigate.

Data Privacy,
Local & Encrypted Protection.

Your files are instantly wiped from memory upon conversion completion. We utilize high-standard SSL 256-bit encryption to ensure the entire process remains within an absolute digital black box.

GDPR Compliant
Zero Logs Policy

100% Free & Accessible

Direct browser-based processing with zero fees. Accelerate your productivity instantly.

Privacy-First Local OCR

Your files are never uploaded to a server. All vision recognition logic is performed locally within your browser for complete security.

VLM Engine 4.0

Supports structured output reconstruction, precisely restoring every cell and paragraph style.

WORD
Technical Support

MOBI Reconstruction
Deep Tech Insights.

Learn how iLoveOCR handles MOBI layout reorganization, font embedding, and privacy security.

01 Will the layout be messy after converting RAW to Word?
iLoveOCR utilizes an advanced VLM semantic reconstruction engine specifically optimized for complex layouts in RAW. The system automatically identifies headers (H1-H3), text wrapping, and multi-column logic, ensuring the generated .doc file possesses a native document flow that supports free editing without losing paragraph formatting.
02 Can special fonts and handwriting in RAW be recognized?
Our built-in deep learning models automatically match the closest standard system fonts. Even if the RAW contains handwritten contracts, stamp text, or low-resolution scans, it will be rendered as clear, searchable, and editable text in Word, significantly reducing manual data entry costs.
03 Will official seals, signatures, and illustrations in RAW be lost?
No. All non-text elements in RAW (such as illustrations, colored seals, and handwritten signatures) are extracted with high fidelity and embedded as independent floating objects in Word, preserving their original DPI resolution without compression.
04 Can I convert and merge multiple RAW files into a single Word document?
Yes. You can batch upload multiple RAW files. The system will perform OCR recognition sequentially and generate either individual documents or a single, continuous Word document based on your preference.
05 Does it support multi-language mixed layouts within RAW?
Perfectly. We support 110+ languages, including mixed Chinese-English, Japanese, Korean, and Arabic. The system automatically detects the languages and invokes the corresponding OCR models to ensure special symbols and grammatical logic are correct in Word.