The problem: TMS platforms charge per-word and per-seat, and their machine translation lacks product context. A typical SaaS with 500 strings across 9 languages costs $200-500/month.
How it works: - Extracts strings from your codebase (XLIFF, JSON, PO, YAML) - Diffs against previous translations (only translates what changed) - Sends to any LLM (Claude, GPT-4, Gemini, Ollama) with your product context, glossary, and style guide - Commits translations back to your branch
Key technical bits: - Structured generation for ICU message format (CLDR plural rules handled correctly - Russian 4-form, Arabic 6-form, etc.) - Hash-based caching to avoid re-translating unchanged strings - Provider-agnostic interface - swap LLMs without config changes
GitHub: https://github.com/webdecoy/ai-i18n
Happy to answer questions about the ICU handling, prompt design, or anything else.
