AI-powered translations
you can actually ship
Use context enrichment, AST-level analysis, styleguides, and integrated checks to translate your app—so quality holds up in languages you don't speak. All from the command line.
By Jan Amann
Author of next-intl
How it works
A pipeline, not a black box
Great translations need more than a model. Every string moves through dedicated steps that prepare, review, and verify.
- 1
AST-based linting
Your source code and messages are analyzed at the AST level—catching missing translations, unused messages, broken ICU arguments, and more.
- 2
Source text review
Source copy is reviewed for spelling, grammar, and styleguide adherence before mistakes can fan out into all your other languages.
- 3
Context enrichment
Ambiguous wording, domain-specific terms, and placeholders are enriched with their intent as context, so translation works from knowledge instead of guesses.
Built-in translation
eloqnt/engine
Context-aware translation with locale-specific styleguides attached, plus post-translation checks for accuracy, consistency, and formatting.
Translation management system
Integrated Crowdin support
Localization outgrowing your repo? Crowdin adds reviews, integrations, collaboration, and more—your catalogs and context carry right over.
The bottom line: Would you merge unreviewed code? When you tell your agent to “just translate”, it does what it's told. But quality needs a gate. eloqnt/studio is that gate—and your agent is welcome to use it too.