Direct your next drop’s campaign with the Tiara AI On-model Photography 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 token timing, 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 replaces trial-and-error prompting with repeatable settings that match fashion production needs. You select lens, framing, lighting, mood, and visual style as controls, then generate on-model stills that stay garment-led and consistent for storefront grids.

That matters when you update hundreds of SKUs: your pipeline can generate batches via REST API with predictable output behavior, then publish with signed provenance and watermarking cues that keep review cycles tight.

Because you can keep the product brief and regenerate consistent on-model imagery without new studio days or shipped samples. RAWSHOT is designed for fast iteration across variants while maintaining garment fidelity and model consistency.

Instead of rebooking timelines, teams adjust UI controls and run batches—then verify outputs with C2PA-signed provenance and an audit trail per image before anything goes live.

You click through a shoot recipe: choose camera lens, framing (full body, half, close-up, detail), pose, angle, lighting, background, and a visual style preset. The generation follows the garment details you set, so the outfit stays true while you direct the look.

That workflow is straightforward for operators: run one-off shoots in the browser GUI, then switch to REST API when you need the same visual direction across many items.

Prompt roulette usually trades reproducibility for variety, which is risky for product pages. With RAWSHOT, you don’t negotiate with a free-text field; you set precise controls that keep cut, colour, pattern, and logo aligned to the garment.

DIY generations can introduce invented logos, drifting garment details, or different faces between outputs—problems that create refunds and manual clean-up. RAWSHOT pairs consistent generation with provenance, watermark cues, and catalog-scale repeatability.

Every RAWSHOT still includes C2PA-signed provenance and watermarking cues, plus AI labelling so teams can apply their review process with clarity. This isn’t a marketing add-on—it’s part of how the output is delivered for downstream use.

For commercial work, it also helps internal stakeholders understand what was generated and why, which reduces last-minute compliance uncertainty when publishing across channels.

Check garment fidelity first: verify cut, colour, pattern, and any branding matches your product. Then confirm framing and lighting fit the campaign or catalog layout, and review the AI labelling and signed provenance for your publishing rules.

Because the workflow is controlled by UI settings and supports consistent models across SKUs, you can also spot issues earlier—before you generate dozens of variants in a batch pipeline.

For stills, pricing is per image with an expectation of about ~$0.55 per image and ~30–40 seconds per generation. Tokens never expire, failed generations refund their tokens, and you can cancel from the pricing page.

That makes it easier to forecast workloads for product teams: run one-off tests in the GUI, then scale with REST API when you’ve locked your visual direction.

Yes. RAWSHOT provides a REST API designed for catalog-scale pipelines, while still keeping the same product-led generation behavior that you use in the browser GUI.

That means production teams can automate nightly runs, store generation metadata alongside SKUs, and apply the same provenance and watermarking cues consistently across the catalog.

Use the browser GUI to define your visual direction with clicks, then hand the chosen look settings to a REST API batch workflow for SKU volume. This keeps decision-making human-friendly while preserving operational consistency.

For example, campaign operators can approve lighting and style presets, and catalog operators can run the same generation recipe across variants, then publish with C2PA-signed provenance and full commercial-rights clarity.