Direct your next pocket square drop with the Pocket Square 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.

Garment-led control keeps cut, colour, pattern, logo, fabric, drape, and proportions aligned to the product you’re selling. That means fewer surprises across variants, and less time spent correcting drift when you refresh seasonal pocket square listings.

In RAWSHOT, you click framing, lens feel, and visual style while the garment stays the brief. You can save settings for repeat runs and keep composition logic consistent between the browser GUI and REST API pipeline.

Save the synthetic model once and reuse it across your entire catalog, so the face and body stay consistent between SKUs. This avoids the “close enough” problem where each output looks like a different person, making listings feel mismatched.

RAWSHOT is built for that workflow: you generate with the same model, then vary garment and visual direction through UI controls. For scale, you can reproduce the same recipe through the REST API without rebuilding creative intent each time.

Reshooting every SKU is expensive, slow, and often still produces inconsistencies across sets and lighting. RAWSHOT gives you a repeatable, garment-faithful way to generate new pocket square imagery for updates without booking studio days.

Because you direct the shoot with buttons and presets, you can create multiple looks per SKU while maintaining consistent framing and model settings. When you’re updating catalogs, that predictability matters more than “one-off” clever outputs.

Yes. You direct the shoot with UI controls for framing, camera angle, lighting, background, mood, and visual style so the pocket square appears in the composition you’re targeting.

The workflow is still product-first: the garment-led engine is engineered to represent your real cut, colour, pattern, and fabric behavior. Generate from the browser for single jobs, then move to the REST API for catalog-scale batches.

Every output includes provenance signalling through C2PA-signed records, plus multi-layer watermarking (visible and cryptographic) and AI-labelled output. That gives publication-ready clarity for teams that need traceability without manual documentation.

RAWSHOT also provides a signed audit trail per image, so you can retain a clear record for review, archiving, and operational QA. When you publish pocket square imagery across PDPs and campaigns, the file carries the story with it.

Start with garment fidelity: verify cut, colour, pattern, and logo placement match your product. Next, confirm model consistency for the SKU set, then check framing, aspect ratio, and visual style against your brand guidelines.

On the compliance side, verify the outputs carry the expected provenance and watermark cues so your publishing process remains auditable. Finally, keep your settings reproducible by using the same saved controls across the batch you plan to upload.

Yes. Photo generation is flat per image at about ~$0.55 per image, with ~30–40 seconds per generation, and tokens never expire. If a generation fails, tokens are refunded, so you’re not forced into guess-and-retry budgeting.

For video and model jobs, token economics differ, but still remain transparent. For photo-heavy catalog updates, the per-image structure keeps planning simple when you scale variants.

Use the REST API when you need consistent batch output with the same garment-led direction. You send the controls and product-led settings, then receive generated stills with provenance, watermark cues, and repeatable composition logic.

This is how ecommerce teams avoid manual re-briefing: the GUI supports single shoots for art direction, while the API supports nightly pipelines for catalog-scale refreshes. Your SKU updates follow the same operational recipe each time.

If a generation fails, RAWSHOT refunds the tokens for that failed generation. That keeps iteration practical, because you can refine controls and regenerate without eating the cost of errors.

You can also cancel quickly from the pricing page, which helps when you’re testing new lighting, aspect ratios, or visual styles for pocket square campaigns. The goal is controlled experimentation with predictable cost behavior.