Direct campaign-ready on-model imagery with the Beret 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 turns photography direction into repeatable operations for SKU pages. Instead of reshooting every variant, you keep garment-led controls and generate consistent on-model imagery that matches your merchandising needs.

Use framing, lighting, and visual style presets to produce stable outputs for category grids and PDP tiles, while each image carries C2PA-signed provenance, watermarks, and AI labelling so your publishing process stays auditable.

Because updates don’t wait for studio availability. With RAWSHOT, you can generate new on-model shots per variant on demand and keep the same brand direction through UI controls and reusable model settings.

The garment stays the brief—cut, color, pattern, logo placement, and drape are represented faithfully—so you avoid the unpredictable drift you typically get when outputs are guided by free-form text.

You start a new shoot, then click your lens, framing, pose, angle, lighting, background, and visual style. The app translates your selections into the generation controls, so you’re directing the shot instead of composing a sentence.

After generation, download 2K/4K stills with C2PA-signed provenance, visible and cryptographic watermarking, and AI labelling, plus a signed audit trail per image for QA before publishing.

Prompt roulette is unpredictable: garments drift, logos can be invented, and faces can change across outputs. Garment-led control keeps the product representation stable so your beret looks like your product, not like a “similar” one.

RAWSHOT also provides synthetic model labelling and a signed audit trail, which helps teams align creative work with compliance and brand trust requirements.

You get full commercial rights to every output, permanent and worldwide. That’s designed for commerce teams who need a clear publishing stance for PDPs, campaigns, marketplace listings, and brand libraries.

Because outputs include provenance signalling and watermarks, your internal review doesn’t start from uncertainty—you can validate assets quickly and keep an auditable record per image.

Verify garment fidelity, confirm the model consistency you selected for your SKU set, and check the labelled provenance signals attached to each image. RAWSHOT’s signed audit trail per image helps you do this systematically in production workflows.

Then validate composition (framing, lighting, background) against your merchandising standard. When you keep direction in UI controls, revisions are faster because you’re changing settings, not reinterpreting prompts.

Still images cost about ~$0.55 per image and generate in roughly 30–40 seconds per output. Tokens never expire, and failed generations refund tokens so you don’t pay for dead ends.

For teams iterating styles and backgrounds, this pricing model keeps creative testing predictable, and the cancel button on the pricing page gives you direct control over ongoing runs.

Yes. RAWSHOT supports a REST API for catalog-scale pipelines alongside a browser GUI for single-shoot direction, so your team can use the same production-grade controls in both modes.

Every output remains labelled with provenance signals and watermarks, and the signed audit trail per image supports operations that need traceability when shipping at SKU volume.

Reuse the same model configuration and iterate through UI controls first, then scale the same direction via the REST API. That keeps your faces and composition stable across variants, so your beret catalog doesn’t look like different photoshoots.

When your pipeline runs nightly, you still maintain clear provenance and labelling on every asset, with per-image pricing, token rules, and an audit trail that helps your QA stay focused.