Author: Yuri Tsverkun
Founder at OCR Craft
Over 15 Years of Experience in the Translation Industry

In today’s translation business, speed often becomes the enemy of quality. Most vendors promise instant PDF conversion at the click of a button, but project managers know the true cost of that kind of “automation”: hundreds of unnecessary tags in CAT tools, broken segmentation, and hidden formatting that turns the translator’s job into a fight with the file.

At our company, we have chosen a different path. Our approach is built on three pillars: the power of OCR tools, the craftsmanship of manual formatting, and intelligent AI support.

Our method: Why “automatic” layout reconstruction is a trap

Most OCR programs try to automatically recreate the layout: fonts, indents, columns. The result is “dirty” code inside the document. Our gold-standard workflow looks different:

  • Recognition with OCR tools: We use this tool as the world’s best character digitization engine.
  • Plain-text extraction: We do not retain automatic formatting. Instead, we extract clean text without hidden clutter.
  • Layout reconstruction from scratch: Our specialists manually rebuild the document structure, styles, and tables in Word.

This guarantees a perfectly clean file in which every tag is relevant, and segmentation is logical. Even in such a process, however, we sometimes encounter areas where traditional methods are powerless.

Where classical OCR falls short: Pattern matching compared

Traditional OCR tools rely on pattern matching. They examine a group of pixels and search their database for a similar letter. If the document is low-resolution, has stains, or uses a specific handwritten font, the algorithm fails. The result is text rife with errors or, worse, “garbage” made up of random symbols, for example, when the letter “A” turns into “@”.

What is the secret of Vision AI?

Where classical OCR sees only unclear smudges, we bring in Vision AI and new-generation multimodal models. They work differently: they do not just analyze pixels, they understand context.

  • Semantic deduction: If a word is partially obscured, Vision AI does not try to guess individual letters. It analyzes the whole sentence. If the model sees the phrase “The installation should be performed by a professional”, it instantly restores the words “should” and “performed” because it understands grammar and linguistic logic.
  • Handwriting recognition (HTR): Handwritten notes in the margins of legal or medical documents have always been a blind spot for automation. Vision AI, trained on millions of handwriting samples, can decipher cursive with accuracy approaching that of a human.

Surgical precision and accountability

We use AI exclusively as a “surgical tool” for short, complex fragments. Why not for the entire text? Because AI is prone to hallucinations, it may confidently replace one illegible digit with another. Since we work with many languages, proofreading large volumes of AI-generated text is a major risk. That is why every fragment recognized through AI undergoes mandatory verification by our specialists.

Shared responsibility for quality

Despite all the innovation, our rule remains unchanged:

High-quality input = High-quality output.

Technology is not magic, but an amplifier. Even the most advanced AI cannot guarantee 100% accuracy on pixelated garbage. We ask our partners to provide clear source files so that our manual formatting and intelligent tools can deliver flawless results.

We do not simply convert files. We prepare them for life inside your workflow. The combination of OCR tools’s reliability, the cleanliness of manual formatting, and the intelligence of AI allows us to solve tasks that others turn down.