Direct your next on-model campaign with the AI On Model Video 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 invented garment inventions.

You gain motion-ready reels per variant while keeping garment details stable across iterations. Instead of scheduling reshoots for each season update, you select scene settings and generate new takes in a repeatable pattern.

In RAWSHOT, video scenes are built from UI controls that map to camera motion, framing, lighting, background, and model action. The result is consistent outputs you can batch via the REST API while maintaining a clear provenance trail for publishing.

Because traditional video production is slow and budget-heavy when your catalog changes weekly or nightly. A studio day may be great once, but it doesn’t scale with SKU churn.

RAWSHOT is designed for repeatable generation: you direct the shoot with visual controls and keep the garment as the brief. Each output is labelled and watermarked, so your legal and brand workflows stay aligned even when you generate frequently.

You don’t start from a text description. You select the garment-led inputs and then set the scene via controls for motion, framing, lighting, and background.

Use the browser GUI for single lookbooks or short marketing drops. For catalog-scale work, the REST API applies the same scene logic, so the batch behaves like a scripted version of your click-driven setup.

Yes when consistency matters. Prompt-driven tools often trade away garment fidelity and reproducibility, which creates extra QA work when you publish across many SKUs.

With RAWSHOT, you direct camera and framing through dedicated controls and keep the garment as the brief. Outputs are C2PA-signed and watermarked, with AI labelling and a signed audit trail per image, so your team can trust what it’s publishing.

Labelled provenance turns generated assets into accountable production artifacts. When your team can see C2PA-signed evidence and watermarking cues, it’s easier to follow brand policy for reviews and release.

RAWSHOT includes visible and cryptographic watermarking plus AI labelling on every output. That clarity supports compliant asset handling for commercial use worldwide with permanent rights.

Start by validating garment fidelity in the final clip: cut, colour, pattern, logo, and drape should match your product files. Then confirm the scene direction—framing, lighting, and model action—fits the channel aspect ratio you plan to publish.

Finally, verify publication-ready provenance cues: C2PA signatures and watermarking should be present, and the clip should be labelled as generated. Use the same saved model setup for each SKU run to reduce face and framing variation.

Video is priced by duration, so cost scales with clip length. RAWSHOT charges about ~$0.22 per second of video and about ~$0.55 per image for stills, with typical generations taking ~50–60 seconds for video.

Tokens never expire, and failed generations refund their tokens. You can also cancel in one click from the pricing page, which keeps your spend predictable during rapid iteration.

Yes. RAWSHOT supports a REST API for catalog-scale pipelines while keeping the same scene controls you use in the browser GUI.

That means your dev or ops team can batch generation across many SKUs and apply the same visual style presets and framing rules. You also keep provenance and rights handling consistent at scale with per-image signed audit trails.

The GUI is for directing single reels quickly; the REST API is for producing them in bulk with the same logic. Teams often start in the browser to lock the visual direction, then move to API batch jobs once the look is approved.

Either way, the garment-led controls remain the core workflow, and your outputs stay labelled with C2PA-signed provenance and watermarking. That separation lets operators ship faster while keeping QA and compliance steps consistent across roles.