Direct your next drop’s shoot with the Optical Frame 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 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.

It turns garment-led direction into a repeatable workflow you can run across hundreds or thousands of SKUs without losing product alignment. Instead of re-shooting when season assets change, you keep the same shoot controls and generate new frames to match your catalog cadence.

With RAWSHOT, you click camera, framing, lighting, and visual style presets while the garment stays the brief. That makes it easier to maintain consistency for listings, marketplaces, and seasonal updates.

Because your bottleneck is usually photography availability, not garment readiness. When you have to book studios, wait for samples, and schedule shoots, the catalog updates arrive late—or with compromises that customers notice.

RAWSHOT replaces that bottleneck with browser controls for single-look direction and a REST API for catalog-scale pipelines. You generate on-model assets using the same controls so new variants stay aligned with your existing product page style.

You upload the garment, then direct the shoot through the interface: set lens, framing, pose, lighting, background, and a visual style preset. The output is built around the product details you provide rather than around language interpretation.

That click-driven workflow keeps iteration predictable—generate, review, adjust, and regenerate. For each SKU, your team can follow the same control set so approvals focus on the garment and brand direction, not on prompt rewrites.

Because prompt-based workflows are inherently variable: the product can drift, branding can be invented, and faces can change between outputs. For ecommerce, inconsistency creates extra QA work and can even lead to customer trust issues.

RAWSHOT is engineered around the real garment—cut, color, pattern, logo, fabric, and drape stay faithful. You also get transparent synthetic models and provenance cues, so your outputs fit the way commerce teams actually publish.

Yes—RAWSHOT outputs include C2PA-signed provenance and watermarking cues, with AI-labelled metadata attached to the image. That gives your publishing workflow an auditable record instead of relying on guesswork.

For commerce teams, this matters because approvals and compliance checks need evidence, not just aesthetics. You also get a clear commercial-rights story for every output, permanent and worldwide.

Start with garment fidelity: verify cut, color, pattern, logo, and fabric cues match your intended product. Then check model and styling consistency across the set so your brand identity stays stable for customers.

Finally, validate the provenance and watermark cues are present and readable for your internal process. RAWSHOT’s signed audit trail per image helps you keep approvals systematic instead of subjective.

Still images typically generate in about 30–40 seconds, priced at roughly $0.55 per image. Tokens never expire, and failed generations refund tokens so your iteration doesn’t become a budgeting guessing game.

You also have a one-click cancel path from the pricing page, which keeps account handling straightforward. For team workflows, this means you can run controlled experiments per collection without getting trapped in vague “usage” terms.

Yes. RAWSHOT provides a REST API so you can generate on-model assets as part of nightly or on-demand catalog pipelines instead of relying on manual browser sessions.

The important part is that you keep the same kind of controls used in the GUI, which makes output consistency easier to enforce at scale. Teams can batch by SKU, generate variants, and send results directly to storage and publishing systems.

That’s the design: the GUI is for directing shoots, and the REST API is for repeating that direction at catalog scale. Your team can start with a few looks, lock the visual style, and then scale the same approach across your SKU set.

When you keep the same controls and review cadence, production becomes a pipeline instead of a series of ad-hoc experiments. Combined with signed provenance and clear commercial rights, it’s built for teams that publish frequently.