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Creative Strategy
5 min read

Inside a Real Brand Shoot: DIY Draft vs. Final Output

A side-by-side comparison of a fashion accessories brand's initial in-house AI draft and the polished, high-fidelity production version.

Side-by-side comparison of DIY AI draft and professional final creative

Case studies work better than claims, so here's one, told straight.

A fashion accessories brand came to us after a few months of running their own AI content in-house. They weren't doing anything wrong, exactly — they'd learned the tools, they had a visual identity in mind, and their draft set was recognisably on-brand. But a few specific things weren't landing:

Lighting consistency across the catalogue

Each product had been shot in its own session with its own lighting logic, so the store page read as slightly disjointed — like different photographers had handled different items.

Texture and material accuracy

Leather and metal hardware — the actual tactile detail that reassures a shopper about quality — was flattening out in a way that made the products look slightly cheaper than they were.

If you already have product photos but no video content, Kurama Studios can turn those assets into polished product videos for ads, reels and landing pages.

Kurama Studios helps ecommerce brands create AI-powered product photography, video ads, reels and campaign assets from the product imagery they already have.

Production speed

New SKUs were taking days each to get through their internal pipeline, which meant the catalogue was permanently a few weeks behind what they'd actually launched.

What changed in production

We rebuilt the set against a single locked lighting and colour reference, so every product — old and new — reads as one continuous shoot. Material rendering got a dedicated pass focused specifically on texture fidelity for leather and metal. And because the pipeline is built for repeat production rather than one-off sessions, new SKUs move from brief to finished set in under 48 hours.

The brand's own draft wasn't a failure — it was a reasonable first pass that surfaced exactly the problems production experience solves for. That's usually how this goes: DIY gets you close enough to see precisely what the gap is.

Full case studies with visuals available on request — useful to see side-by-side if you're evaluating where your own set currently sits.

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