Direct your next on-model reel with the AI Try On Video Generator—every setting is a click, not a typed brief.

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 control the shot with fixed scene options: camera motion, framing, lighting, background, model action, shot count, duration, aspect ratio, and resolution. Each choice is a UI control, so your team can repeat a look without learning any prompt syntax.

In practice, you set the take to match your publishing channel (like vertical or square), then generate a labeled try-on reel that keeps your garment as the brief for cut, color, pattern, and logo.

Because the settings are structured controls, the same scene recipe can be applied across SKUs, instead of relying on free-form prompt variation. This matters when you publish multiple product variants in a single launch window and need consistent try-on presentation.

RAWSHOT’s garment-led generation plus stable model identity and controlled takes help you avoid drift between exports that typically shows up when DIY prompting iterates by trial and error.

Reshooting each update is slow, expensive, and logistics-heavy, especially when product pages need new imagery on tight calendars. With RAWSHOT, you generate new on-model try-on reels in browser controls and, when needed, scale them through the REST API.

That workflow keeps review predictable: your team can adjust framing, lighting, and motion for each release while keeping the garment faithful to the original product parameters.

It can replace many studio days for try-on visuals because RAWSHOT provides controlled lighting and camera framing choices that your team can rehearse in a browser interface. You still stay in charge of creative direction, and you get labeled outputs with clear provenance for publishing.

Use it for campaign assets where the garment must stay accurate—then reserve studio time for what truly needs human capture beyond the look you can direct in RAWSHOT.

Every output includes C2PA-signed provenance and AI-labelled labelling cues, plus visible and cryptographic watermarking signals. That gives commerce teams a clean story for review and downstream handling, not just an image file with no audit signal.

RAWSHOT is designed for EU AI Act Article 50 and California SB 942 contexts, and it keeps compliance cues attached to what you publish so approvals can happen faster.

You get full commercial rights to every output, permanent and worldwide. That makes procurement and brand/legal review easier because the rights story is explicit rather than inferred from output type.

For try-on video specifically, you can build consistent scenes per SKU and publish without re-negotiating rights each time you generate a reel for a new colorway or campaign cut.

Video pricing is per-second, and each generation typically takes around tens of seconds depending on your selected duration. Tokens never expire, so teams can plan long-running pipelines without worrying about time-based token loss.

If a generation fails, the tokens are refunded, and you can cancel with one click from the pricing page—keeping iteration costs predictable for ecommerce operations.

Use the REST API for batch pipelines while keeping the same scene-building logic you use in the GUI. That allows your team to run high-SKU schedules without manual click-through for each variant.

For catalog operations, the combination of REST scale, audit trail signals, and stable take controls helps you ship on time while maintaining consistent presentation across thousands of products.

DIY prompting relies on typed creative text, which often leads to garment drift, invented branding, or inconsistent faces across outputs. Even when you get a good first result, reproducibility across SKUs usually requires repeated prompt iteration, which slows production and complicates QA.

RAWSHOT instead uses garment-led controls and scene presets for directorial consistency, then attaches provenance and watermarking cues so what you generate is reviewable and publishable with less operational friction.