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AI Act Translation Guidelines: How to use Lara Translate effectively

  1. Always review the output: While Lara Translate delivers high-quality translations, occasional inaccuracies or ambiguities may occur.
  2. Ideal use cases: General content, marketing materials, business communications, and technical documentation.
  3. For legal, medical, or highly sensitive content: We recommend a human review to ensure full compliance and precise terminology.
  4. Use glossaries and translation memories wisely: They are powerful tools to ensure consistency and domain accuracy. However, if the contents of glossaries or memories are incorrect, the translation output may be compromised or misleading.
  5. Consider content style and tone: Lara supports different translation styles (e.g., formal, fluid, creative) to better match your needs.
  6. Provide context carefully: While adding instructions or extra context can improve translation accuracy, excessive or irrelevant instructions may cause the output to diverge significantly from the original text. Use this feature thoughtfully.
  7. Typos are often understood, but better to write correctly: Lara can handle common typos or minor spelling errors, but clear and correct input ensures more precise translation results.
  8. Use editable source files for document translation: To preserve formatting as accurately as possible, always upload editable originals instead of scanned PDFs or images.
  9. Check language pairs with special formatting needs: For example, bidirectional scripts (like Arabic or Hebrew) or character-based languages (like Chinese or Japanese) may require formatting adjustments.
  10. Avoid relying on AI output as final without human oversight in regulated contexts: Especially when translations have legal or contractual consequences.
  11. Report any issues: If you notice unexpected output, our support team is available to help investigate and improve quality.

This article is about: 

  • How to get reliable results with AI translation

  • When human review is still important

  • How to provide good input for better output

  • Common mistakes to avoid