Direct your next drop with the AI Floodlight Lighting Generator—clicks, not prompts, for garment-led campaign and catalog imagery.

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 replaces prompt roulette with repeatable direction. You choose the camera lens, framing, background, and a lighting preset, so each variant stays aligned to your brand’s lookbook or PDP standard.

Instead of fighting inconsistent outputs, you iterate in controlled steps: generate floodlight-inspired lighting tests, review garment fidelity, then export at 2K/4K with your required aspect ratios—ready for campaign and storefront use.

Because lighting changes shouldn’t force a full production cycle. RAWSHOT keeps the garment as the brief while you adjust creative controls to generate new imagery that matches your direction.

This matters for commerce teams managing many variants at once: you can keep the same model face across SKUs to prevent drift, then batch new shots through the interface or REST API without booking studio time.

You upload the garment reference and then direct the scene with the RAWSHOT controls—framing, pose, angle, background, and lighting. Each change is applied as an explicit setting, so you don’t depend on a model improvising your product.

Once you’ve dialed the look, generate and review 2K/4K output. Then publish with confidence using signed provenance and watermarking cues built into every image.

Garment fidelity is built into the workflow, not left to chance. RAWSHOT is engineered around the real product, so the cut, color, pattern, and drape stay represented faithfully when you adjust lighting and style.

With DIY prompting, garments can mutate between outputs, which breaks SKU consistency. RAWSHOT’s catalog-friendly consistency plus per-image auditability makes your review process faster.

Yes. RAWSHOT outputs are designed for publishing-grade governance: they’re C2PA-signed, watermarked (visible and cryptographic), and transparently AI-labelled so teams can comply with internal and platform requirements.

For campaign operators, that means you can prepare floodlight lighting shots with a clear rights and provenance story—without scrambling to justify what was generated after launch.

Check garment fidelity, framing fit, and the visual match to your selected lighting preset. Because RAWSHOT provides controlled settings, you can verify that the product details remain correct across compositions.

Then confirm provenance and watermarks are present, and review the signed audit trail for operational QA. This keeps approvals consistent across your team’s roles.

Photo generation is priced per image, around $0.55 per image, with about 30–40 seconds per generation. Tokens never expire, and failed generations refund their tokens so you don’t lose budget on rejects.

Cancel is one click from the pricing page, which keeps experimentation safe for small teams. That cost model is built for repetitive SKU workflows, not one-off stunts.

You use the REST API for batch generation when you need many SKUs or frequent updates. The GUI gives you a single-shoot workflow, while the API turns the same kind of controlled settings into production pipelines.

This keeps your floodlight lighting direction consistent across runs so you can refresh PDP imagery on schedule. It’s also easier for commerce engineering to monitor and review because the workflow is structured.

RAWSHOT is designed for catalog consistency, with stable model identity across SKUs so faces and body presentation don’t drift between shoots. That helps keep your product line visually coherent when you publish across many PDPs and channels.

In practice, teams generate a set of floodlight look tests, lock the approved lighting and style choices, then scale through the interface or API for ongoing updates. That flow ends with predictable approvals and fewer retakes.