Direct your next activewear drop with the AI Activewear Video Generator, directed by clicks—not text.

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.

You get on-model motion that stays anchored to the actual garment, so your product presentation is consistent across channel formats. Instead of repeating a full studio cycle for each update, you generate reels from your real SKU and adjust shot controls in the application.

RAWSHOT pairs click-driven scene building with garment-led representation, plus C2PA-signed provenance metadata and visible + cryptographic watermarking cues. For teams, that means fewer surprises before publish and a clearer internal workflow from batch generation through review.

Because seasonal refreshes are usually a packaging problem, not a new photoshoot problem. With RAWSHOT, you update the garment input and keep the rest of the look consistent through saved model settings and reusable scene controls.

This reduces drift between variants and keeps catalog motion aligned with your existing brand direction. Every output includes audit trail and commercial-rights framing, so production and legal review don’t become separate bottlenecks.

In RAWSHOT, you upload/select the garment and build the reel using presets for camera, framing, lighting, background, and model action. Each decision is a control in the interface, so you can move fast while keeping the outfit faithful to the product brief.

Then you generate and review labelled outputs with signed provenance metadata and watermarking cues. When you switch aspect ratios or visual styles, you’re directing the same scene system, not rewriting a text instruction.

Because garment-led control reduces the two biggest failure modes of prompt-driven workflows: outfit drift and brand-detail surprises. With generic image AI, garments can mutate, logos can be invented, and the final look can diverge from your intended SKU.

RAWSHOT keeps cut, colour, pattern, logo, and drape faithful to your provided garment, and it supports stable model reuse across SKUs. The result is fewer “close enough” renders and a more reproducible pipeline for PDP updates.

Yes. Outputs include C2PA-signed provenance metadata and visible plus cryptographic watermarking cues, and the platform provides a clear commercial rights story for every generation.

That matters for publishing governance because your teams need labelled AI video before it goes live, not after the fact. RAWSHOT also maintains a signed audit trail per image/video so reviews can trace what was generated and when within the workflow.

Do a product-first verification: confirm cut, colour, pattern, and logos match the garment you intended. Then verify framing and lighting are consistent with the template you built for your campaign or PDP layout.

Finally, review labelling and provenance cues—C2PA-signed metadata, watermarking signals, and the signed audit trail per output. With RAWSHOT, you can trust that the release asset includes those governance markers by default.

Video pricing is straightforward: ~$0.22 per second of video, with typical generations around ~50–60 seconds per reel. Tokens never expire, and failed generations refund their tokens so you can iterate without silent cost creep.

Compared to stills, longer clips consume more tokens per second, so pick durations intentionally and reuse scene presets across SKUs. When you’re ready, cancel in one click from the pricing page if you need to pause a pipeline.

Yes. RAWSHOT includes a REST API designed for catalog-scale pipelines, so production teams can generate video reels in batch workflows while keeping the same garment-led scene controls.

This is how you connect asset preparation, SKU updates, and publishing automation without switching creative systems. You can still direct single reels in the browser GUI for quick approvals, then move the same rules into the API for nightly runs.

Creative owns the look system—styles, lighting direction, and scene presets—while operations owns batching, scheduling, and review. In RAWSHOT, both roles use the same control language, because the interface maps directly to scene decisions.

That separation makes throughput predictable: you can generate through the GUI for quick iterations, then switch to REST API pipelines for higher volume. The built-in labelling, provenance, and commercial rights framing keep approvals clean as output counts grow.