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# The Localization Engineering Platform

Max Prilutskiy·Updated about 1 month ago·2 min read

Lingo.dev is an AI-powered localization engineering platform. It helps product engineers turn LLMs into stateful translation APIs - to produce consistent, production-grade translations for apps, docs, and content across every language.

## Context and Localization Engineering

Using LLMs for translation is obvious. Any team can send a string to a model and get a translation back. What makes translations _perfect_ is two things: **context** and **localization engineering**.

**Context** is what the model knows beyond the string itself - the product, the audience, the brand voice, the locale-specific conventions. Without it, the model guesses. With it, the model localizes.

**Localization engineering** is the practice of encoding that context into reproducible infrastructure - glossary rules, formality preferences, cultural adaptations - so every translation, across every locale, applies them consistently.

Without both, you get translations. With both, you get localization.

## The Problem

Before LLMs, teams had two options - both flawed.

**Machine translation** was fast but structurally incapable of understanding product context. Teams shipped MT output knowing it would erode trust in every market.

**Manual translation** was accurate but scaled linearly. Every new locale required training linguists on product terminology, brand voice, and domain concepts. After processing 100M+ words across 42 languages, we found that 89% of localization delays happen in handoffs between teams, not in translation itself.

Both treated localization as a project management workflow. Lingo.dev treats it as an engineering concern.

## What You Build

On Lingo.dev, teams build their own localization engines. Each engine combines:

- **LLM models per locale** - Pick the right model for each language pair with ranked fallbacks.
- **Brand voice** - Define how your product speaks per language. Formal "Sie" in German, informal "tu" in Italian, polite "vous" in French.
- **Glossary** - Map source terms to exact translations per locale. "911" becomes "112" for European markets. Product names stay untranslated.
- **Instructions** - Encode linguistic rules generic models miss. Adjective positioning in Spanish, space before percentage signs, pronoun formality per market.
- **Quality scoring** - GEMBA scores, BERTScore, glossary compliance, locale-specific validators. Continuous, automatic.

The result: teams use their own unique insights and preferences - combined with Lingo.dev's language engineering research, ongoing since 2023 - to scale globally from day one, predictably, in languages they don't speak.

## Open Source Developer Tools

The Lingo.dev open-source community (5,100+ GitHub stars) builds developer tools that connect codebases to localization engines:

- **CLI** - Translate from the command line. From install to first translated build in 4 minutes.
- **CI/CD** - GitHub Actions, GitLab CI, Bitbucket Pipelines. Translations ship with your code.
- **Compiler** - Build-time i18n. No runtime overhead, no layout shift.
- **I18n MCP** - Localization awareness for AI coding assistants: Claude Code, Cursor, GitHub Copilot.

## Next Steps

- [Localization Engines](/content/en/docs/platform/engines/index.html)\ 
  Learn how engines combine models, glossaries, brand voice, and scoring
- [AI Reviewers](/content/en/docs/platform/ai-reviewers/index.html)\ 
  Set up automated translation quality monitoring
- [CLI Quick Start](/content/en/docs/cli/index.html)\ 
  Install the CLI and run your first translation
- [API Reference](/content/en/docs/api/index.html)\ 
  Integrate the localization API into your workflow