Vision-first OCR for Complex & Multilingual Documents

NextOCR recognizes text directly from visual signals — without relying on dictionaries or language-model post-correction.

Built for CPU-only environments, on-prem deployment, historical documents, and low-resource scripts.

Try the Demo Training / Roadmap Contact
Trusted by: Google EFEO ACLEDA Bank Plc. Credit Bureau Cambodia
CPU-first
No GPU required • deploy on low-cost servers
Continual Learning
Improves as new documents are processed
Multilingual
Khmer core • scalable to SEA scripts

Why Vision-first OCR?

Many OCR systems are language-first: they depend on dictionaries, spell-checking, or large language models to “fix” recognition. This can distort original spelling and fails on historical variants, names, and domain-specific terms.

Language-first OCR (common)
  • Heavily relies on lexicons / correction
  • May “normalize” or alter original spelling
  • Struggles with rare words & historical orthography
Vision-first OCR (NextOCR)
  • Recognizes characters as they appear in the image
  • Preserves original spelling and structure
  • Works better for complex scripts & historical documents

Especially important for Khmer and other scripts with high orthographic variation, including historical and manuscript sources.

Continual Learning by Design

NextOCR is built for continual learning: it adapts to new layouts, fonts, document types, and writing styles over time — not a one-time training event.

Archive & Heritage
Palm-leaf manuscripts • historical scans
Government & Legal
Stable • auditable output
Banking OCR
On-prem • privacy-friendly

Continual learning enables OCR quality to improve as real-world documents are processed, while keeping deployment practical for CPU-only servers.

Multilingual Training Roadmap

Khmer is the core focus. NextOCR is designed to expand into more languages within one vision-first framework.

Khmer (core) English Vietnamese Chinese Lao Myanmar

Other languages are actively being trained and evaluated.

Use Cases

  • Historical manuscripts, palm-leaf texts, and archival scans
  • Government gazettes, legal documents, and official publications
  • Banking and financial OCR (on-prem / privacy-sensitive)
  • Multilingual document digitization pipelines
  • Vision-Language Model (VLM) pipelines built on reliable OCR signals

Contact

Get in touch for demos, pricing, or technical discussions.

  • Email: danhhong@gmail.com
  • Phone: (+855) 95 333 409
  • Telegram: t.me/hout18