Direct garment-led campaign-ready imagery with the Onesie 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.

You stop reshooting or re-packaging garments every time you need a new PDP image. RAWSHOT keeps the garment as the brief—so cut, color, pattern, logo, fabric, and drape stay faithful while you vary camera, framing, pose, and style.

Instead of prompt roulette, your team repeats the same controls across variants and saves models for consistency. Each output includes provenance metadata and a signed audit trail so approvals are faster and publishing is easier to defend.

Because generic image runs often drift: garments mutate, branding can be invented, and the face changes between outputs. For commerce publishing, those inconsistencies create rework and undermine catalog coherence.

RAWSHOT is built around garment fidelity and catalog-scale consistency, with C2PA-signed provenance and clear commercial-rights framing. You also get a predictable per-image token flow with refunds for failed generations, so iteration stays operationally manageable.

Upload the product context, then direct the take using the shoot controls: lens, framing, pose, camera angle, lighting, background, mood, and visual style. The interface swaps the prompt box for application-grade settings so your creative intent stays legible and repeatable.

Generate stills in 2K or 4K and pick the aspect ratio you need for PDP and ads. If you’re working at catalog scale, the REST API lets you reuse the same model and settings across SKUs.

Yes. You can save a model once and reuse it across your catalog so the face and body stay consistent from SKU to SKU, avoiding the “close enough” feeling that forces retakes.

This model consistency pairs with garment-led control so the product changes with your variant inputs while the presentation stays stable. The result is a coherent catalog where updates don’t require a whole new shoot plan.

RAWSHOT includes C2PA-signed provenance metadata and output labelling cues, plus visible and cryptographic watermarking. Each image is paired with a signed audit trail you can keep through approval and publishing.

That means compliance teams don’t have to reconstruct what happened after the fact. The workflow is designed so provenance is attached to the deliverable, not missing until someone asks later.

Check garment fidelity first—cut, color, pattern, logo, and drape should match your product brief. Then verify style alignment for the channel you’re posting to, and confirm the output’s provenance and audit trail are present for your review process.

Because the shoot is directed through fixed controls, you can iterate systematically: change lighting or background while keeping the model consistency you need for a catalog look. That reduces the cycle time spent redoing work that drifted in uncontrolled generations.

Photos price per image, and generation runs in roughly 30–40 seconds per output with a predictable token flow. Tokens never expire, and if a generation fails you get token refunds instead of silent loss.

On the operator side, you also get a one-click cancel control, so experimentation doesn’t turn into a billing surprise. For teams iterating across size and color variants, that makes planning practical.

Yes. RAWSHOT supports a REST API for catalog-scale generation, while the browser GUI is available for single-shoot work. That means the same garment-led controls can power both ad-hoc edits and automated pipelines.

For catalog ops, consistency is the win: reuse the same model, apply your style rules, and batch-produce stills for collection launches. You also keep clear provenance and commercial-rights framing per output for downstream publishing steps.

Design and product teams direct the creative settings—camera, framing, lighting, mood, and visual style—using the GUI controls. Catalog ops then runs batch generations through the REST API to create consistent assets across SKUs.

Review happens with provenance and signed audit trails attached to each image, so approvals are grounded in deliverable metadata. When the pipeline is live, updates become operational: adjust settings, regenerate variants, and publish with confidence—without rerunning a full studio schedule.