Direct your next abaya shoot with the Abaya AI On-model Photography Generator—campaign-ready imagery directed by clicks.

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 your garment details into predictable, publish-ready on-model visuals you can regenerate as often as you need. Instead of waiting on reshoots, you can iterate framing, lighting, and style per SKU while keeping the abaya representation anchored to the product.

RAWSHOT is built around the garment-led brief and pairs that with synthetic models that are transparently labelled, plus C2PA-signed provenance and watermarking cues. The result is creative iteration that operations can schedule, version, and export without guessing what changed between outputs.

Because reshoots are slow, expensive, and hard to standardize across a catalog. When you change season details, you typically lose continuity in model look, lighting, and framing—then spend more time reworking images to match your existing store layout.

With RAWSHOT, you direct a click-driven shoot setup, save models for consistency, and generate new stills at ~30–40 seconds per image. Each export carries signed audit trail metadata, so your team can update quickly while maintaining a clear provenance record.

You start by selecting the composition controls: framing, pose, camera angle, lens character, lighting, background, and a visual style preset. Those choices are UI-driven, so you’re not crafting prompt text to coax the right framing.

RAWSHOT then generates on-model imagery with garment fidelity—cut, color, pattern, logo, fabric character, and drape represented faithfully. Before publishing, you can verify style preset alignment, ensure the product focus matches your PDP needs, and export images with C2PA-signed provenance and watermarking cues.

Yes, because it reduces randomness. Prompt-based workflows often lead to garment drift, invented branding, or inconsistent faces between runs, which forces retakes or manual fixes before images go live.

RAWSHOT keeps the garment as the brief and uses UI controls for camera, angle, and light so teams can repeat a look across SKUs. It also supports SKU consistency by letting you save the synthetic model configuration, which helps prevent the “close enough” problem.

They are, by default. Every image includes C2PA-signed provenance metadata plus AI labelling signals, and the output is watermarked with visible plus cryptographic cues that support internal governance.

For an abaya catalog, that means your compliance workflow doesn’t start with reverse-engineering what happened in generation. You also get a signed audit trail per image, which helps teams document creative provenance when publishing across marketplaces and internal channels.

Start with garment-led verification: confirm cut, color, pattern, and logo placement match the product you sell. Then check composition basics like framing, aspect ratio, and product focus so PDP crops look intentional rather than accidental.

After that, review provenance and disclosure signals: C2PA-signed metadata, watermarking cues, and AI labelling should be present in your exports. When you generate at catalog scale, these checkpoints prevent the common failure modes that come from untracked, prompt-only output variation.

Still images are priced per output—about ~$0.55 per image—and generation typically takes ~30–40 seconds. Tokens never expire, so your team can batch work when it fits your production schedule.

If a generation fails, the tokens are refunded, which reduces the cost of iteration during styling and QC. You can also cancel in one click from the pricing page, keeping cost control straightforward for product teams and admins.

Yes. RAWSHOT supports catalog scale through a REST API while still offering a browser GUI for single-shoot directions. That means your team can prototype creative controls in the GUI and then automate the same garment-led workflow for nightly pipelines.

For abaya catalogs, this approach keeps SKU production repeatable because you’re not relying on prompt text that can drift between runs. Exports carry signed provenance and watermark cues, so your downstream tooling receives assets with clearer governance and traceability.

Use the same click-driven settings as a shared production language. Designers pick framing, light, and style presets that match the brand direction, while ops and catalog teams manage batch generation through the REST API.

Because outputs include C2PA-signed provenance, watermarked disclosure cues, and a per-image signed audit trail, compliance can review exports without guessing what changed. This workflow scales from browser experiments to automated catalog launches while keeping rights framing consistent for publication worldwide.