Inside the Translation Engine: Glossaries, Style Rules, and Smart Retranslation

Rasepi's translation engine sets itself apart by focusing on translating individual blocks rather than entire documents, allowing for efficient use of resources and customization per tenant. When a document is edited, the system identifies changes through content hashing and only retranslates altered blocks, applying tenant-specific glossaries, style rules, and formality preferences. Glossaries, treated as mutable runtime artifacts in DeepL, are managed locally and synced when necessary, while style rules can be updated in place, offering flexibility for iterative refinements. The engine respects human edits by marking them as 'stale' rather than overwriting, and translations are orchestrated based on triggers that dictate timing, such as immediate retranslation or translation upon first access. This architecture not only reduces costs but also maintains consistency across translations by integrating terminology, style, and formality settings, ensuring that machine-generated translations align closely with the company's language standards. The same engine also supports Rasepi's conversational interface, ensuring consistent language quality in both written and spoken interactions.

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