Direct your feed looks with the AI Instagram Feed Generator—click-driven, garment-faithful, and C2PA-signed.

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 changes the workflow from reshoot-driven production to variant-ready generation with the garment as the brief. You click to set framing, lighting, and visual style, then generate consistent imagery per SKU without prompt roulette.

Because RAWSHOT keeps model consistency and provides signed provenance and watermarked outputs, catalog teams can publish faster while maintaining a clean evidence trail for each image and its intended use.

Reshoots are expensive, and generic tools often drift between outputs—so your catalog ends up with mismatched looks, faces, or even altered product details. RAWSHOT is designed around garment fidelity, with consistent direction controls you can reuse across variants.

That means fewer production cycles when you update a colourway, swap a print, or refresh campaign content. You get repeatable visuals with auditable provenance instead of chasing re-rolls to make the product “close enough.”

Upload the garment, then direct the shoot with the interface: choose lens, framing, pose, angle, lighting, and background from presets. You’re not writing a sentence; you’re clicking the production settings that shape the final composition.

RAWSHOT also supports 2K and 4K outputs and a wide style preset library so you can match campaign goals quickly. Each generated image includes signed provenance and watermarking cues, making it safer to publish across channels.

Because prompt roulette invites drift—garments can change, logos can be invented, and faces can vary across generations. RAWSHOT keeps garment fidelity as the primary constraint and lets you iterate via click-driven controls that stay consistent from SKU to SKU.

That consistency helps ecommerce teams maintain uniform presentation across listings while avoiding the time sinks of re-prompting and QA. You also get labelled outputs with signed audit trail records and clear commercial-rights framing.

Yes. RAWSHOT outputs are C2PA-signed with watermarking cues and AI-labelled provenance, and every image carries an audit record so your publishing workflow has traceability. That’s valuable for teams that need brand-safe attribution across social and ecommerce.

Beyond compliance, it’s also practical: you can standardize approvals because each output follows the same signed process. RAWSHOT provides full commercial rights to every output, permanent and worldwide, for ongoing campaign use.

Start by verifying garment fidelity: cut, colour, pattern, logo, fabric, and drape match the uploaded product. Next, confirm the direction settings you selected—framing, lighting, mood, and visual style—match your catalog standard.

Finally, rely on provenance and auditability: each output includes signed records and watermarking cues so you can keep approvals consistent. With RAWSHOT, the model consistency layer also reduces rework from face or pose variation across SKUs.

For still images, RAWSHOT is priced at about ~$0.55 per image with ~30–40 seconds per generation. Tokens never expire, and failed generations refund their tokens, which keeps experimentation manageable for ecommerce teams.

RAWSHOT also supports a one-click cancel flow on the pricing page so you can stop a run without getting stuck in per-seat or “contact sales” gates. When your team iterates often, that predictable unit economics matters.

Yes. RAWSHOT offers a browser GUI for single-shoot work and a REST API for catalog-scale pipelines, so your production team can batch-generate imagery without manual re-direction each time. You get the same garment-led control model across both interfaces.

This is built for repeatable operations like nightly SKU updates and synchronized campaign packs. Because outputs are signed with provenance and include audit trail records, the API path stays safe for commercial publishing.

It fits well because direction happens through clear UI controls that designers can operate and catalog ops can standardize. You can keep model consistency across your catalog, then use the GUI or API depending on whether you’re doing a one-off shoot or a batch pipeline.

That division of labor reduces friction: designers click to set the look, while ops rely on provenance signalling, watermarking cues, pricing transparency, and rights framing for smooth approvals. The result is fewer retakes, less drift between SKUs, and faster content readiness.