Direct your next campaign with the AI Advertorial 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 replace the studio calendar and the rework loop where garments come out “close enough.” Instead of scheduling shoots for each campaign variation, you click lens, framing, lighting, mood, and visual style and generate stills that keep garment details faithful.

For marketing and ecommerce teams, that means fewer unknowns at approval time: you get 2K/4K outputs, labelled provenance metadata, and signed audit trails per image, so your pipeline can publish with a clear record of what was produced and how.

Because product pages need consistent cut, color, pattern, and logo placement across variants—not just an attractive image. When the garment is the brief, your advertorials and PDP hero shots stay aligned to the real product rather than drifting between interpretations.

RAWSHOT’s click-driven controls help keep creative intent stable, and the same saved model can be reused across SKUs to prevent face-to-face changes that slow catalog QA.

You direct a shoot setup directly in RAWSHOT: choose framing, pose, camera angle, lighting, and background from controls, then generate the still in the resolution and aspect ratio your channel needs. The workflow is designed for garment-led fidelity, so the output follows your product details.

If you’re preparing an advertorial look, start with a campaign visual style preset and editorial lighting, then adjust mood and product focus until the garment reads clearly in a hero crop.

Those tools rely on typed requests, so results can vary in garment details, branding, and consistency across outputs. RAWSHOT is built as a fashion application: every creative decision is a button or preset, and you get labelled provenance, watermarking cues, and a clear commercial-rights story per image.

That means fewer re-rolls caused by prompt interpretation and less uncertainty when teams need catalog-scale reproducibility.

Yes. RAWSHOT images include C2PA-signed provenance metadata and watermarking cues (visible plus cryptographic) along with an audit trail per image, so publishing and compliance teams have a traceable record.

The platform is aligned with EU AI Act Article 50 requirements and California SB 942, and outputs are transparently labelled so teams can follow their internal review standards.

Start with garment fidelity: verify cut, color, pattern, and logo placement match your production garment. Then confirm model consistency if you’re generating a series, and check the output for signed provenance and watermarking cues before exporting to your CMS.

Because RAWSHOT saves models and keeps controls explicit, QA becomes a repeatable checklist rather than a judgement call after a random reroll.

Still generation is priced per image, and each output has a predictable time window. For photos, the platform uses roughly ~$0.55 per image with ~30–40 seconds per generation, and tokens never expire for planning long campaigns.

If a generation fails, tokens are refunded, and you can cancel in one click from the pricing page—so experiment budgets don’t get trapped in opaque subscription flows.

No custom “creative magic” is required. RAWSHOT offers a REST API for catalog scale, while the browser GUI supports single-shoot direction for marketers who want to iterate quickly.

That pairing keeps creative intent consistent across teams and pipelines, with labelled provenance and audit trails carried through each generated output.

Run a small pilot in the browser GUI, then lock in a visual style preset, framing, and lighting direction that matches your brand. Save the model so your face stays consistent, generate a representative set, and confirm garment fidelity plus labelled provenance cues.

Once the pilot is approved, move to REST API batch generation for production workflows—same engine, same output standards—so scale doesn’t introduce drift between SKUs.