AI can speed up multilingual content, but quality and safety decide if it helps or hurts. Here’s how we deploy AI for localization with measurable quality.

When AI helps (and when it doesn’t)

• High-volume UI strings and support content with clear style guides.
• Not for legal, pricing or nuanced sales pages without human review.

Terminology management

• Build a shared glossary per product domain and locale.
• Enforce terminology during generation and post-editing.

LQA workflow

• MT/AI draft → human post-edit → second review for high-stakes pages.
• Checklists: brand tone, terminology, functionality (dates, units, currency).
• Sample-based audits for low-risk content; full review for money pages.

Toolchain

• TMS + style/term enforcement, translation memory, connectors to repos.
• Redaction for sensitive data; audit logs for compliance.

Metrics that matter

• Edit distance per locale and content type.
• Error rates by category (term, grammar, meaning, functional).
• Time to publish vs. baseline; impact on conversion per locale.

Risks and mitigation

• Hallucinations → constrain prompts, use memories/terms, human review.
• Privacy → process locally or via compliant vendors; redact PII.
• Drift → periodic re-baselining of style and examples.

Next steps

If you need multilingual content at quality, not just speed, we can help.

• Get a free assessment → /freequote
• Talk to an engineer → /meet
• Start localization → /contact