Tony Sellprano

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CzechChecker: Grammarly for Czech

AI for Complex Languages

CzechChecker: Grammarly for Czech

Internal Experimental Project

AI Mastery of Complex Czech Grammar

Engineered custom fine-tuned LLMs to provide Grammarly-like corrections for the notoriously difficult Czech language.

Exceptional Linguistic Accuracy

Achieved high-precision corrections on nuanced grammatical edge cases, impressing native speakers with its capabilities.

Valuable Product-Market Fit Insights

Though technically successful, this MVP provided critical learnings on market adoption for specialized AI language tools.

Overview

Czech is one of the most grammatically complex languages in the world, with layered cases, gendered words, aspectual verbs, and endless exceptions. Tools like Grammarly simply don't exist for Czech.

So we built CzechChecker—a native alternative trained specifically to understand and correct Czech language structures using fine-tuned OpenAI models.

What We Did

We fine-tuned OpenAI language models on Czech data to create a tool that could handle the subtle and often ambiguous rules of Czech grammar. Instead of relying on rules or generic spellcheckers, our model learned how Czech is actually written and spoken.

The tool worked in real time, correcting:

  • Grammatical gender and number agreements
  • Verb aspect and conjugation
  • Case usage
  • Common spelling and punctuation errors

Features

  • AI-powered grammar and spelling correction for Czech
  • Clean web-based editor for typing or pasting content
  • Real-time suggestions and scoring
  • Embedded video demo explaining the tool in use

Video Demo

Outcome

The MVP worked incredibly well from a technical standpoint. The accuracy and nuance of the model's corrections surprised even native speakers. But despite strong core functionality, the product didn't gain enough traction.

We ultimately discontinued the project due to lack of product-market fit—but it remains one of our most technically impressive builds, especially considering the linguistic challenge.

What We Learned

  • Czech NLP requires deeply specialized training and attention to detail
  • Even high-performing AI tools can struggle with adoption if the pain isn't widely felt or monetizable
  • Video demos are invaluable for showing subtle features in a language product

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