Human Review of AI-Generated Copy for ZURU Toys

ZURU built a custom AI pipeline to generate product copy for part of their spring-summer 2026 toy range: 58 products, 17 brand lines, 22,000 words, eight markets. Before any of it reached packaging or retail listings, they had every word reviewed and rewritten by creative translators with category knowledge.

The Challenge

ZURU built a custom AI pipeline to generate product copy for part of their spring-summer 2026 range: 58 products, 17 brand lines, 22,000 words, destined for packaging and retail listings across eight markets. Before any of it went live, they commissioned a full expert review. That is a sensible step for any team producing multilingual copy at this scale.

Product copy for toys has to work in two directions. It needs to give a parent confidence and it needs to make a child want the product. Getting the tone right in English is one thing. Getting it right in eight languages, across markets with different retail conventions, different cultural references and different audiences, is where AI has to prove itself. AI tools can detect many issues in translated copy. What they cannot do is decide how to fix them: how to rewrite copy so it carries the right energy for a specific brand in a specific market, or how to assess whether the output is appropriate for the audience it is going to reach. That is the work ZURU needed done.

Our Approach

Creative translators with experience in toy and children's consumer products reviewed the full English source and all eight translated outputs. The brief was not to correct errors in isolation. Each piece of copy was assessed against its purpose: does this make a parent trust the product? Does it make a child want it?

Each language was treated as a separate brief, with its own starting point and its own set of decisions. Across all eight markets, the issues were distinct rather than uniform. Some required structural rewriting. Some required decisions about how brand names and product terminology should be handled for that market. Some required assessment of whether the copy was appropriate for a children's audience. The approach in each case was the same: understand what the copy needed to do, then make it do that.

Across all eight languages, the standard was the same: copy that feels like it was written for that audience, in that market, for that product.

What We Delivered

• 22,000 words of AI-generated source copy reviewed across 8 languages
• 58 products reviewed, corrected and rewritten in Chinese Simplified
• 17 ZURU brand lines covered, including XSHOT, 5 Surprise, Bunch O Balloons, Smashers and Rainbocorns
• All product copy fields addressed: titles, descriptions, features, keywords and warnings
• Language and market-specific issues identified and resolved across all 8 languages
• Copy delivered ready for use on packaging and retail listings across all 8 markets

Navigating the Complexity

At this scale, across this many markets and brand lines, the complexity is rarely in any single error. It is in the cumulative effect of copy that has been produced without an audience in mind. Every language had issues that were specific to that market. None of them were the kind that a quality score or fluency check would surface. Each one required a translator who understood the language, the market and the product category well enough to know what correct looked like.

The consistent finding across every language was that the AI had translated the words without writing for the market. Accuracy and fitness for purpose are not the same thing.

The Outcome

Across all eight languages, the AI output preserved meaning but carried English sentence structure, phrasing and rhythm into the target language. The result was copy that read as translated rather than native, and in a consumer category where tone is as important as accuracy, that gap matters. Every language output was reviewed, corrected and rewritten where needed before delivery.

• Product copy reviewed, corrected and rewritten across all 58 products and 8 languages
• Every content type addressed: titles, descriptions, features, keywords and warnings
• Market and audience-specific issues resolved in every language before delivery
• All 8 languages delivered ready for packaging and retail listings

How We Can Help

Using AI to translate copy across multiple markets doesn't end the question of quality. It moves it. The output still needs human review. The question is whether the people doing that review are creative translators who know the market and know the category.

A quality score won't tell you when copy is technically accurate but wrong for the audience. That takes judgement. That is what we bring.