How-to · Inclusive sizing
Inclusive fashion brands need imagery showing the same garment on a range of body types, ethnicities, and ages — but a traditional inclusive shoot is the most expensive shoot to produce (more models, more fittings, more days). This guide walks through using Apiway's creator marketplace to generate diverse on-model imagery from one garment photo, with body proportions and skin texture that stay realistic at every size because the underlying creator sessions are real photographs.
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Before opening Apiway, write down the size and demographic range your brand wants to represent — e.g. sizes XS through 4XL, ages 20–55, three skin-tone bands, two body shapes per band. Inclusive imagery without a defined range becomes inconsistent token representation; the range definition is the editorial work.
Open Explore and filter / browse for creators whose photo sets fit each cell of your range. Save creators that cover plus-size and mid-size bodies, multiple ethnicities, and age bands you've defined. Apiway's marketplace ships diverse creator sessions specifically because the team prioritizes that supply — vs. pure-AI tools where 'diversity' is generated from text and often falls into uncanny-valley body proportions at non-mid sizes.
Open Reference Photoshoots, upload the garment, and run the generation against each creator from the saved set. The hybrid pipeline preserves each creator's real body proportions — a plus-size creator's session produces a plus-size on-body output, not an AI guess at how a plus-size body fits a garment. That distinction is what makes the imagery defensible as genuinely inclusive.
Inspect each output at 100% zoom: shoulder line, sleeve length, garment drape across torso, hemline. If any output's drape doesn't match how the garment would actually fit that body, regenerate or pick a different creator from the saved shortlist. Inclusive imagery loses credibility instantly when the garment fit looks fake at any size — be ruthless on QA.
On Shopify or your storefront, attach the size-diverse outputs as a multi-image PDP gallery (or as a 'see it on different bodies' carousel below the hero). Buyers convert significantly higher when they can see a garment on a body shape close to theirs — that's the whole conversion case for inclusive imagery beyond the brand-values argument.
Run each generated variant through Image Creation to produce 4:5 (Feed) and 9:16 (Reels / TikTok) versions. Inclusive social campaigns convert harder than studio-shot single-model campaigns; the asset pipeline above produces a month of inclusive social content from one garment in one afternoon.
Approximately 200–400 credits at default settings (1 garment × 6–8 saved creators across the size and demographic range). At 1 credit = $0.01 USD that's $2–$4 per garment for an inclusive PDP gallery — vs. $5,000–$25,000 to book the equivalent inclusive studio shoot. The Studio plan (14,000 credits / month) covers ~30 garments at this cadence, which is enough for a typical seasonal capsule.
Yes — every creator in the marketplace ships with the same documented commercial license (creator → Apiway → buyer). Inclusive campaigns specifically benefit from this rights chain because diverse model imagery is one of the most-litigated areas in fashion advertising; pulling images from Pinterest or stock for diversity coverage creates legal exposure that the marketplace eliminates.
Lalaland.ai generates diverse models from prompts — the model is fully synthesized. Apiway's creators are real photographed people. For inclusive content the distinction matters most: synthesized plus-size models often have proportions that look 'AI' to a human viewer, especially at edges of the size range. Apiway's approach trades the marketing claim of 'unlimited synthesis' for the credibility of real bodies in real sessions.
