Direct your next try-on reel with the AI Virtual Try On Video Generator—clicks, not prompts.

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 camera and the clip structure through real scene settings: camera motion, framing, background, lighting, shot count, and duration. You also select model action presets so the motion matches your product story without asking the system to “guess” your intent from text.

Because these are UI controls, the look stays consistent across iterations. That matters when you need multiple variants (colors, sizes, styles) to feel like the same campaign asset pack.

RAWSHOT is engineered around the garment you upload, so cut, colour, pattern, logo, fabric, and drape stay aligned as you adjust scene controls. When you regenerate, you’re changing the direction (camera/lighting/background), not replacing the product with an imagined interpretation.

This is the operational difference between product-led creative and prompt roulette. Instead of re-debugging wording, you dial in the scene until it fits the commerce goal, then repeat the same approach across your catalog.

Publish workflows need clarity, not ambiguity. RAWSHOT provides C2PA-signed provenance plus visible and cryptographic watermarking, and AI-labelled outputs so your downstream teams (legal, marketing, marketplaces) know what they are working with.

That transparency supports compliance practices and internal audit trails, which is especially important when try-on video is used across ads, PDP carousels, and brand channels where attribution expectations are stricter.

Yes—save a model once and reuse it across your catalog so faces and body characteristics stay consistent from SKU to SKU. That prevents the “different person in every reel” problem that can happen when you generate assets ad hoc.

For teams running frequent updates, consistency is a conversion lever. It keeps your variant grid looking intentionally produced rather than assembled from separate iterations.

Use the aspect ratio selector and framing controls before you generate. Your clip can be built for destinations like 9:16, 1:1, 4:5, or 16:9, and you can switch between full body, 3/4, half body, and close-up framing.

This makes it practical to reuse a single production intent across TikTok Reels, Instagram feeds, and PDP placements without rethinking composition from scratch each time.

DIY prompting relies on typed instructions, and small wording changes often lead to inconsistent garments, invented details, or shifted faces across outputs. That creates extra cleanup and re-shoot-like overhead even when the tool is “fast.”

RAWSHOT keeps your creative decisions in click-driven controls and anchors the brief to the actual garment. You also get provenance and audit trail signals alongside a clear commercial rights story for publishing.

Video pricing is per second of video, with about ~$0.22 per second, and each generation typically takes ~50–60 seconds depending on clip settings. Tokens never expire, and you can cancel in one click from the pricing page.

On failed generations, tokens refund automatically. That means you can iterate on scene direction without turning cost management into a guessing game.

Yes. RAWSHOT supports both a browser GUI for single reel creation and a REST API for catalog-scale pipelines. You can use the same garment-led creative controls while batching across many SKUs.

For commerce teams, that’s what turns visuals into infrastructure. You can schedule nightly runs, generate variant packs, and keep output settings consistent instead of depending on manual button-by-button work.

Verify the garment fidelity by spot-checking cut, colour, pattern, logo, and drape in the generated clip. Confirm provenance signals (C2PA-signed record and watermarking cues) so your internal compliance workflow stays clean.

Then validate model consistency for the campaign’s catalog context and ensure your usage rights align with your publishing plan. With full commercial rights, permanent and worldwide, teams can publish with fewer last-minute approvals.