Direct campaign-ready fashion imagery with clicks — with the Wrap AI On-model Photography Generator.

Never—you direct every output with sliders, presets, and clicks on the garment, not typed prompts. That UI control is consistent across GUI and REST API payloads, which is why ecommerce teams onboard buyers without rewriting creative briefs as chat threads.

For catalog teams, reliability matters more than model cleverness; RAWSHOT keeps tokens, timings, refund rules, commercial rights framing, provenance signalling, watermarking cues, REST surface, and SKU-scale batch patterns explicit so operations can rehearse PDP launches without hallucinated garment inventions.

It gives you repeatable direction for garments at catalog volume. Instead of reshuffling results from variant to variant, you click stable settings (camera, framing, lighting, and style) and generate on-model stills built around the product brief.

For merch and catalog ops, the practical win is consistency: save and reuse the model so faces and body alignment don’t drift between SKUs. Pair that with labeled outputs and full commercial rights, and you can publish faster while keeping your governance story clean.

Because you can generate new stills without booking studio time or shipping samples cross-continent. When your store needs colorways, size ranges, or seasonal variants, RAWSHOT turns the garment into the brief and keeps your art direction repeatable.

You select lighting, background, and visual style presets, then iterate quickly. Each output includes signed provenance metadata and watermarking, so marketing and compliance teams get clarity alongside speed.

You start with the product composition you want, then direct the scene using RAWSHOT controls. Pick framing (full body, half body, close-up, flat lay), select lens and angle, choose pose and lighting, and lock a visual style preset.

The garment-led workflow reduces surprises because the product representation is handled as part of the system, not as a natural-language instruction. Generate stills in 2K or 4K, export, and keep your rights and labeling trail attached to every file.

Prompt-based tools often trade away control for creativity, and the garment can mutate between outputs. RAWSHOT keeps the garment as the brief while you direct the scene with UI settings that stay stable across iterations.

That stability matters for product fidelity: cut, color, pattern, and drape should match the actual garment. With RAWSHOT’s labeled provenance and full commercial rights, you also reduce downstream uncertainty about what was generated and how it can be used.

Yes. Every RAWSHOT image carries C2PA-signed provenance metadata and multi-layer watermarking, including visible and cryptographic layers, so teams can document what they published.

That supports transparency expectations connected to EU AI Act Article 50 and California SB 942, and it helps commerce teams build consistent workflows for marketplaces, paid ads, and brand governance. You’re not guessing whether a file is eligible—you have the labeling trail attached.

Start with garment fidelity and composition: confirm the cut, color, and pattern match your product, and verify the framing (full body, close-up, detail, flat lay) fits your PDP layout. Then review the model consistency setting if you’re covering many SKUs in a single release.

Finally, rely on the file’s built-in provenance and watermarking cues to satisfy review workflows. Because the outputs come with signed audit trail per image and clear commercial rights terms, approvals become faster and more repeatable.

For still photos, the price is per image—about ~$0.55—and generation typically takes around 30–40 seconds. Tokens never expire, so you can batch work without worrying about time windows.

If a generation fails, tokens refund, and you can cancel in one click on the pricing page. Video and model workflows can cost more because they consume more tokens per second, but stills are designed for fast per-image iteration.

Yes. RAWSHOT supports a browser GUI for single shoots and a REST API for catalog-scale pipelines, using the same garment-led engine. Teams can send batch jobs with the same control intent and keep outputs aligned across thousands of SKUs.

That means fewer manual steps between generation and publication. With per-image audit trail and labeled provenance, ops teams can trace outputs back to their generation runs while keeping governance intact.

Designers can direct art direction inside the GUI by selecting lighting, framing, and visual styles, then save settings for repeatability. Merchandisers and production ops can run catalog-scale generation via REST API for consistent SKU coverage and predictable token economics.

Because each output carries signed provenance and full commercial rights terms, approvals don’t require re-litigating what happened in generation. The workflow stays coherent from click-based exploration to operational batch publishing.