Brand-Consistent Translation Using LLMs

An AI translation solution for a global retailer, crafted to enhance their multilingual advertising with brand-consistent voice, offering a cost-effective alternative to traditional agencies.

Brand-Consistent Translation Using LLMs

The Opportunity

A prominent global retailer was grappling with the challenge of translating its advertising content into a multitude of languages. The traditional approach involved a manual process with the reliance on external translation agencies.

The client expressed a strong interest in exploring the capabilities of Large Language Models (LLMs) to produce translations that not only convey the original message accurately but also maintain the brand's unique style and tone across various languages.

What we did

✔︎ Developed a state-of-the-art digital translation tool powered by advanced GPT models.
✔︎ Fine-tuned the model to ensure superior accuracy and contextual understanding.
✔︎ Designed an intuitive user interface that simplifies the translation editing process and provides in-depth content insights.
✔︎ Conducted rigorous quality assessments of LLM-generated translations, benchmarking them for precision and cultural relevance.

The Results

Evaluations by native speakers indicated that the AI Translation tool's results were authentic and resonated well with international audiences, leading to significant reductions in time and cost associated with the translation process.

3x

as many testers preferred AI over existing translations

How we did it

Over an intensive four-week period, our team developed the translation application utilising FastAPI for dependable backend operations and Gradio for creating a user-friendly interface.

Starting with three principal languages, we compared the app's translations with those from a conventional agency. Native speakers evaluated the outputs for authenticity and precision. We then refined a GPT-3.5 model with targeted translation datasets to elevate its performance further.

Follow-up evaluations by native speakers validated the enhanced quality of the model, demonstrating its ability to provide cost-effective translations that are both accurate and culturally attuned.

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