Direct your next campaign with the AI Gel Lighting 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 lighting direction into repeatable choices you can audit and re-run, not a one-off creative guess. You pick lighting mood, style, framing, and product focus with the same controls every time, so gel-forward looks stay coherent across a set.

That matters when campaign approvals require consistency. RAWSHOT generates 2K or 4K on-model stills with C2PA-signed provenance and visible plus cryptographic watermarking, so your team can iterate gel variations quickly while keeping garment fidelity stable.

Because you want the garment to stay the brief while only the art direction changes—lighting mood, crops, and style. Traditional shoots require retakes, samples, and lead time for each variant, which slows season updates.

RAWSHOT supports the same workflow for one-offs and large pipelines, with consistent synthetic models and garment-led output. The result is faster iteration across SKU sets without losing cut, colour, pattern, logo, or drape accuracy.

You direct the shoot with product focus, framing, and visual style controls, then generate. The system is engineered around the real product so your garment details are represented faithfully instead of being bent to match a text idea.

From a production perspective, you also get clear export expectations: pick 2K or 4K and the aspect ratio for PDP or feeds, and publish with C2PA-signed provenance plus watermarking. Failed generations refund tokens, so experimenting with gel moods stays low risk.

Prompt roulette produces inconsistent outputs because each instruction can nudge the model in a different direction. Garment-led control keeps cut, fabric drape, and branding details stable while you iterate lighting and style via explicit UI controls.

That stability matters for PDP accuracy and customer trust. RAWSHOT also labels synthetic models transparently and provides signed audit trails per image, so your catalog operations can keep approvals consistent across variants.

Every RAWSHOT image includes C2PA-signed provenance metadata and watermarking that supports visible and cryptographic labelling. You can use that for internal review, vendor transparency, and compliance-oriented publishing workflows.

This isn’t a vague statement; it’s a concrete record attached to the output. With RAWSHOT, teams also get signed audit trail records per image and a clear commercial-rights story: full commercial rights to every output, permanent, worldwide.

Start by verifying garment fidelity—cut, colour, pattern, logo, and fabric drape should match the source product. Then confirm framing, aspect ratio, and lighting mood align with the campaign or PDP layout you’re targeting.

RAWSHOT helps by keeping controls explicit and outputs labelled with signed provenance and watermarking cues. For additional confidence, generate a small set per SKU and compare across variants to ensure model identity stays consistent.

Still images are priced per image at about $0.55, with roughly 30–40 seconds per generation. Tokens never expire, and you can cancel with one click from the pricing page if you need to stop a run.

If a generation fails, RAWSHOT refunds the tokens, so experiments with new gel lighting looks don’t permanently burn budget. That predictable economics profile works well for teams generating hundreds to thousands of SKU images across a season.

Yes—RAWSHOT supports both a browser GUI for single shoots and a REST API for catalog-scale pipelines. Your team can direct the same kind of lighting and framing choices through structured requests instead of manual workflows.

Because the app is control-based rather than prompt-based, your production team can standardize outputs across SKUs. You also keep C2PA-signed provenance, watermarking cues, and signed audit trails attached to each image your pipeline exports.

Run the shoot direction in the GUI for quick approvals, then scale with the REST API for nightly or batch runs. Different roles can review outputs using labelled provenance and audit trails without needing to understand any creative prompt logic.

This makes the workflow operationally clean: you iterate lighting and style choices, generate consistent results, and export with full commercial rights to every output. When a run needs to stop, the cancel control is on the pricing page, and failed generations refund tokens.