100% private, client-side grammar, spell, and readability checker for your text.
Early grammar checkers relied entirely on strict, hard-coded rules. A programmer would write a rule saying: "If the word is 'a' and the next word starts with a vowel, flag an error."
While fast, rule-based systems struggle with the complexity and exceptions of human language.
Modern grammar tools (like Grammarly) use Natural Language Processing (NLP). Instead of static rules, they train massive machine learning models on millions of books and articles.
The model learns the statistical probability of words appearing together. If it sees "I is happy", the neural network flags it not because it hit a rule, but because its training data indicates "I am happy" is statistically much more probable in that context.
To run these massive neural networks, modern grammar tools usually require sending every single keystroke you type to their remote cloud servers for analysis.
This presents a major security risk for enterprise users, as sensitive emails, proprietary source code, and confidential documents are constantly streamed to a third-party server.
Why do modern grammar checkers use Machine Learning instead of hard-coded rules?
