Grammarly

Grammarly analyzes text as it's being typed using a multi-pass grammar engine that applies rule-based corrections for grammar, spelling, and punctuation. The system uses a probabilistic language model combined with hand-crafted grammar rules to detect errors across 400+ grammar patterns, then surfaces corrections inline with explanations of why each rule applies. The architecture processes text incrementally without requiring full document submission, enabling sub-100ms latency for single-sentence corrections.

Grammarly's tone detection engine analyzes text across multiple dimensions (confidence, formality, friendliness, optimism) using a neural classifier trained on labeled writing samples. The system maps detected tone to a multi-axis visualization and suggests rewrites that shift tone in specific directions. The implementation uses embeddings-based similarity matching to find alternative phrasings from a curated corpus of tone-variant sentence pairs, then ranks suggestions by semantic similarity and tone alignment.

Grammarly's plagiarism checker compares submitted text against a database of billions of web pages, academic papers, and previously submitted documents using a fingerprinting and semantic similarity approach. The system generates locality-sensitive hashes of text passages and queries a distributed index to find potential matches, then performs fine-grained semantic similarity scoring to identify plagiarized sections. Results are returned with source attribution, match percentage, and side-by-side comparison views.

Grammarly's generative AI capability uses large language models (GPT-based) to generate new text or rewrite existing passages while preserving the user's original tone and style. The system accepts user prompts (e.g., 'make this more concise', 'expand this idea', 'rewrite for a professional audience') and uses prompt engineering combined with style transfer techniques to generate alternatives. The implementation includes a style encoder that captures the user's writing patterns from previous text and conditions the LLM to maintain consistency.

Grammarly's brand voice feature allows teams to define custom writing guidelines (tone, terminology, style preferences) and enforces them across all team members' writing. The system uses a rules engine that matches text against user-defined patterns (e.g., 'always use Oxford comma', 'avoid passive voice', 'use brand-specific terminology') and flags deviations. The implementation stores style guide rules in a configuration layer that integrates with the core grammar and tone detection engines, enabling real-time feedback on brand consistency.

Grammarly provides real-time writing assistance across multiple platforms through a browser extension (Chrome, Safari, Firefox, Edge) and native desktop applications (macOS, Windows). The integration uses DOM manipulation for web-based text fields and native accessibility APIs for desktop applications, injecting correction suggestions directly into the user's writing interface. The architecture maintains a local cache of user preferences and recent corrections to minimize latency, while syncing corrections and settings to cloud servers for cross-device consistency.

Grammarly provides a REST API that allows developers to integrate writing analysis and correction capabilities into custom applications. The API accepts text input and returns structured data including grammar errors, tone analysis, plagiarism scores, and generative suggestions. The implementation uses the same underlying rule engines and neural models as the consumer product, but exposes them through a standardized JSON API with rate limiting, authentication via API keys, and batch processing support for high-volume use cases.

Grammarly tracks and visualizes writing statistics including word count, readability score, vocabulary diversity, and error frequency across all user writing. The system maintains a historical database of writing samples and generates trend reports showing improvement over time. The implementation uses statistical analysis to compute readability metrics (Flesch-Kincaid grade level, etc.), vocabulary analysis via word embeddings, and error categorization to identify patterns in the user's most common mistakes.

Grammarly provides grammar and style checking for multiple languages including English, Spanish, French, German, Portuguese, and others. The system uses language-specific rule sets and neural models trained on native speaker corpora for each supported language. The implementation includes automatic language detection via character encoding and statistical analysis, allowing users to switch between languages or write in multiple languages within a single document. Language-specific tone detection and style suggestions are calibrated to cultural and linguistic norms of each language.