Direct your next drop's campaign with the AI Gobo Lighting Generator.

Never—you direct every output with sliders, presets, and clicks on the garment, not typed prompts. That UI control stays consistent whether you’re using the browser GUI for single looks or the REST API for catalog-scale batches. You spend your time choosing the shoot parameters that matter to fashion teams, like lens, framing, and lighting style, instead of debugging text outputs.

For SKU-scale operations, reliability is the point. RAWSHOT keeps tokens, timing, refund rules, commercial-rights framing, provenance signalling, watermarking cues, and REST surface explicit so ecommerce and catalog teams can run repeatable launches without hopping between prompt versions.

It turns creative direction into repeatable settings your team can reuse across hundreds of products. Instead of re-running “similar enough” renders, you keep the garment on brief—cut, color, pattern, logo placement, and drape stay aligned to your real item. That makes catalog updates faster and less labor-heavy when you swap lighting styles or campaign framing.

In RAWSHOT, you click to set the composition and lighting preset, then generate. You can keep the same model face and body profile for all SKUs, which reduces the manual QA burden that usually comes from inconsistent faces and drifting garment details.

Because traditional reshoots compound cost, scheduling, and shipping time as your catalog grows. RAWSHOT lets you generate new campaign-ready variations from the garment itself, keeping direction controlled through the interface. The result is less waiting and fewer bottlenecks between design, merchandising, and publishing.

You can also keep provenance and audit trails attached to each output, which helps when teams need traceability for brand governance. Generate, label, review, then ship visuals to storefronts and marketing without the cycle of retakes.

You don’t start from text. You select the garment-led setup through UI controls: camera lens range, framing (full body through detail), pose, angle, background, mood, and visual style presets. Then you generate on-model stills that preserve the garment’s real attributes.

For lighting, you pick a lighting preset consistent with your art direction, then adjust composition via click settings. The garment is the brief, so you get fewer “product mutations” than you’d see when generic models react to vague wording.

Because it gives you stable, fashion-specific levers instead of open-ended language. Prompt-based workflows often cause garment drift, invented branding, or inconsistent faces across generations, which breaks PDP consistency. Click-driven controls keep the product details anchored while you iterate lighting and composition.

RAWSHOT also supports direct QA: outputs are C2PA-signed and watermarked, with an audit trail per image. That makes it easier for ecommerce teams to approve visuals quickly and confidently for publishing.

Every RAWSHOT still includes compliance-minded provenance cues: C2PA-signed metadata plus visible and cryptographic watermarking, along with AI labelling. That means your merchandising and legal teams have clearer documentation of what was generated and how it should be treated for publishing.

On top of that, you receive full commercial rights to every output, permanent and worldwide. Combined with the audit trail per image, this creates a cleaner commercial story than DIY rendering pipelines.

Start with garment fidelity: confirm cut, color, pattern, logo placement, and drape match your actual product. Then verify model attributes and consistency for the face/body profile you’re using across SKUs. Finally, check provenance cues—C2PA signing, watermark visibility, and audit trail presence—so your publishing review has a record of the output.

When you find an outlier, you can adjust lighting and framing via the UI controls and regenerate quickly. Failed generations refund tokens, so experimentation stays safer for ops teams.

For photos, pricing is transparent at about ~$0.55 per image, with ~30–40 seconds per still generation. Tokens never expire, and you can cancel instantly from the pricing page if you need to stop mid-workflow. Failed generations refund tokens, so you’re not charged for unusable outputs.

This matters for production planning: you can run controlled iterations across lighting presets and compositions without hidden quotas or unclear metering. It’s designed for teams that need predictable creative throughput, not surprise charges.

Yes. RAWSHOT provides a REST API for catalog-scale workflows while keeping the same garment-led engine behind the scenes. That means you can batch-generate outputs for many SKUs overnight and still rely on the same controls that you use in the browser GUI for single shoots.

Pair the API with your internal review process: approve the lighting direction, then verify the audit trail and watermarking cues before publishing. This reduces manual rework compared with DIY prompt pipelines that don’t carry clean provenance metadata.

The browser tool is for directing shoots and validating look direction quickly. Once your art direction is locked, the REST API lets operations or engineering run the same generation logic across large SKU sets with consistent model profiles. That separation keeps creative review focused while automation handles throughput.

In practice, you can assign one role to approve lighting and visual style presets, while another handles catalog exports, QA checks, and publishing. The shared platform reduces coordination overhead because the interface and output metadata behave the same across one-off and batch production.