Direct your next campaign with the AI Gallery Image Generator, using click-driven controls for your garments.

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 on-model imagery into a repeatable workflow you can run per SKU, per variant, and per aspect ratio—without reshooting every update. Instead of gambling on output drift, you click the same garment-led setup and keep a stable model for the set.

RAWSHOT generates in 2K or 4K, supports every aspect ratio, and returns C2PA-signed, labeled images you can publish with clearer provenance. That means your catalog refresh can stay consistent from one nightly run to the next.

Because traditional shoots are tied to time, samples, and studio days; seasonal refreshes usually force expensive rework. RAWSHOT gives you a controlled production loop where you adjust photography decisions through the interface, then generate new imagery for the changed items.

You can keep the same model face across SKUs, switch visual styles for campaign vs catalog, and reuse the same controls across GUI and REST API workflows. The practical alternative is fewer retakes and faster merchandising.

In RAWSHOT, you direct the shoot with photography controls: lens, framing, pose, camera angle, lighting system, background, mood preset, visual style, aspect ratio, and resolution. Each decision is a click, so you stay in a consistent “shoot language” rather than trialing phrasing.

Then you generate the output and iterate by changing one or two controls at a time. The result is a clean set of carousel and PDP images with garment fidelity and labeled provenance in the outputs.

Garment-led control keeps the product as the brief, so cut, color, pattern, logo, fabric, drape, and proportion stay grounded to your items. Prompt-based tools often bend the image toward the prompt’s interpretation, which can cause garment drift and invented details.

With RAWSHOT, you use the GUI and REST API to keep consistency and reduce rework. That helps teams avoid inconsistent faces across outputs and keeps catalog imagery coherent across variants.

Yes. Every generated image includes C2PA-signed provenance metadata plus visible and cryptographic watermarking and AI-labelled output. That gives your publishing workflow a clear, verifiable story for what each image is.

It’s also aligned with EU AI Act Article 50 and California SB 942 requirements, so compliance-minded teams can handle outputs more predictably. You’re not left guessing what metadata exists or how to document it.

Use garment fidelity and continuity checks first: confirm cut, logo placement, color, and fabric cues match your product expectations. Then verify model consistency across the set so faces and bodies don’t shift between variants.

Finally, validate provenance-related outputs you plan to publish: C2PA signing, watermarking cues, and AI-labelled attribution. RAWSHOT also includes a signed audit trail per image, which supports internal approvals.

For stills, RAWSHOT pricing is flat per image: about ~$0.55 per image, with roughly 30–40 seconds per generation. Tokens never expire, and failed generations refund tokens, so cost planning stays straightforward.

If you cancel, the cancel button is on the pricing page. For teams producing multiple variants, this predictable token model helps keep merchandising timelines realistic.

You can start in the browser GUI for single shoots, then move to the REST API when you’re ready for catalog-scale batches. The REST surface is designed for repeatability, so you can apply the same garment-led controls across many SKUs.

Teams typically wire the API into their existing asset pipeline and batch generation workflow. The key is that output quality and control logic stay consistent between GUI and API runs.

Designers can direct shoots in the browser GUI using photography controls, while catalog operators can scale generation through the REST API. Because everything is click-driven, teams don’t need to become prompt engineers to get dependable output.

That structure supports fast iteration across campaign and ecommerce contexts while keeping model consistency, provenance, and commercial-rights framing consistent. The end result is a workflow your whole team can operate without prompt roulette.