Direct your next campaign shoot with the Rash Guard 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 changes your workflow from “reshoot when the catalog updates” to “generate the next variant on demand.” You can keep presentation consistent—pose, framing, lighting intent, and a stable model—so storefront grids don’t feel mismatched between seasons.

RAWSHOT is built around the garment: cut, color, pattern, logo, fabric, and drape are represented faithfully. Choose a visual style preset and camera framing once, then reuse your setup as you scale across SKUs with the REST API for nightly pipelines.

Because reshoots cost time, logistics, and studio availability—then you still risk inconsistency between batches. When you’re updating a season palette, the goal is controlled change with stable look and layout.

With RAWSHOT, you click through lighting, background, and style presets while keeping the garment as the brief. Save your model setup and reuse it across your catalog so the face and body identity stays consistent as you generate seasonal variants.

You load the garment and direct the shoot through the interface: select lens, framing, pose, camera angle, lighting, background, mood, and a visual style preset. Each control maps to a production decision, so you can reproduce a look across multiple outputs.

RAWSHOT generates labelled on-model imagery with C2PA-signed provenance and watermarking. That means you can publish without building a custom compliance story for each generation attempt.

Generic image models rely on freeform text behavior, which makes garment presentation less controlled across variants. Even when you get “close,” teams often deal with garment drift, inconsistent branding details, and variable outputs that are hard to catalogue.

RAWSHOT replaces the prompt box with click-driven controls tailored to fashion production. It also includes provenance and labelling cues (C2PA-signed records, visible and cryptographic watermarking) plus full commercial rights framing so ecommerce teams can run repeatable pipelines.

Yes. RAWSHOT outputs include C2PA-signed provenance metadata and AI labelling, supported by visible and cryptographic watermarking. This is designed for teams that need traceable records as part of publishing and review workflows.

Each image carries a signed audit trail so you can connect what you generated to the generation instance. That makes review cycles cleaner, especially when multiple stakeholders approve campaign and catalog assets.

Start with garment fidelity checks: confirm cut, color, pattern, and logo placement match your actual product. Then review framing and lighting for readability on your PDP grid—close-ups for texture, half-body for fit cues, and consistent aspect ratios for layout.

Finally, verify provenance signalling: C2PA-signed records and watermark presence should be visible to reviewers, and audit trail should be tied to each generation. RAWSHOT is built to make these checkpoints straightforward and repeatable across variants.

For still images, pricing is per image and generation is typically around 30–40 seconds per output at about ~$0.55 per generation. Tokens don’t expire, and if a generation fails, tokens are refunded.

Video costs more because it uses more tokens per second than stills, and you pay in a time-based way for the clip length. If your workload is PDP grids and campaign stills, stills are usually the most predictable choice.

Yes. RAWSHOT supports a REST API for catalog-scale generation, while the browser GUI works for single-shoot direction. The controls you use in the GUI map to structured generation you can run in batches, so creative intent stays consistent.

This is built for operations: you can run nightly pipelines, manage repeatability, and keep SKU consistency without per-seat gates or per-volume punishment on core features.

Use the same controls across roles: creative or product leads direct the look in the GUI for initial approvals, and production or ops runs the REST API pipeline for catalog volume. That way, approvals are tied to the exact settings you’ll repeat across SKUs.

Because models and settings are reusable, you avoid drift between batches. You also get labelled outputs with C2PA provenance and clear commercial rights framing, so legal and marketing reviews don’t become the bottleneck.