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Rawshot.ai

Catalog-ready · Editorial lighting · SKU consistency

Direct your next line sheet with the AI Wholesale Catalog Generator—click-driven, garment-faithful results in minutes.

Generate consistent on-model imagery for your wholesale catalog with clicks, sliders, and visual presets instead of typed instructions. Keep the garment as the brief so cut, colour, pattern, logo, and drape stay faithful across every SKU. No studio days. No samples. No prompts.

  • ~$0.55 per image
  • ~30–40s per generation
  • 150+ styles
  • 2K or 4K
  • REST API ready
  • C2PA-signed provenance

7-day free trial • 50 tokens (10 images) • Cancel anytime

Line-sheet imagery with controlled styling.
Solution
Try it — every setting is a click
Catalog gloss on light grey
4:5

Direct the shoot. Zero prompts.

Choose a camera, framing, lighting, and visual style. Then generate catalog-grade on-model imagery with garment-led fidelity—no prompt text field to manage. 5 tokens · ~34s per image

  • 6 clicks · 0 keystrokes
  • app.rawshot.ai / new_shoot
Image Composition
app.rawshot.ai / new_shoot
Mood
Pose
Camera angle
Lens
Framing
Lighting
Background
Resolution
Aspect ratio
Visual style
Product focus
4:5 · 4K · Half body
Generate

How it works

Click-driven catalog shoots

Build line-sheet imagery with stable settings, garment fidelity, and provenance—without prompt syntax or reshoots between SKU updates.

  1. Step 01

    Pick the controls

    Select lens, framing, pose, lighting, background, and a visual style preset. Every creative choice is a click, slider, or preset.

  2. Step 02

    Direct the garment-led brief

    Confirm the product focus for the shot composition. The garment stays the brief, keeping cut, colour, pattern, logo, and drape faithful across variants.

  3. Step 03

    Generate and keep consistency

    Generate your line-sheet imagery and reuse the same synthetic model setup across your catalog. Each output ships with provenance, watermarking, and full commercial rights.

Spec sheet

Twelve proofs for catalog trust

From click-driven control to SKU consistency and C2PA provenance, these tiles show what operators can verify before publishing.

  1. 01

    No-likeness by design

    Synthetic models come from 28 body attributes with 10+ options each, making accidental real-person likeness statistically negligible by design.

  2. 02

    Click-driven, zero prompts

    Every creative decision is a button, slider, or preset—camera, angle, distance, frame, pose, facial expression, and light.

  3. 03

    Garment fidelity stays true

    Cut, colour, pattern, logo, fabric, and drape are represented faithfully so your product reads correctly in every catalog panel.

  4. 04

    Diverse synthetic models

    You get diverse synthetic models that are transparently labelled, with a consistent lookbook-friendly variety for your lineup.

  5. 05

    SKU consistency without drift

    Save a model once and reuse it across your catalog so the face and body stay consistent across every SKU image.

  6. 06

    150+ visual styles included

    Choose catalog, lifestyle, editorial, campaign, street, noir, and more—then keep that look aligned across your series.

  7. 07

    2K/4K and every ratio

    Generate at 2K or 4K in all needed aspect ratios, from tight line-sheet crops to full composition layouts.

  8. 08

    Compliance with provenance

    Outputs are C2PA-signed and aligned with EU AI Act Article 50 and California SB 942 requirements, with transparent labelling.

  9. 09

    Per-image audit trail

    Each image includes a signed audit trail so your publishing workflow can verify origin and processing history.

  10. 10

    GUI for shoots, API for scale

    Use the browser GUI for single sets and the REST API for catalog-scale pipelines, both built around the same controls.

  11. 11

    Speed and predictable pricing

    Photo generation runs at about ~30–40 seconds per image for token-based pricing, with tokens that never expire and one-click cancel.

  12. 12

    Full commercial rights

    Every output includes full commercial rights, permanent and worldwide, so you can license images for wholesale and marketing without extra processing steps.

Outputs

Catalog-ready outputs, verified No prompts, just proof.

Preview the look across line-sheet crops, consistent models, and catalog styles—each output carries provenance and watermarking cues.

ai wholesale catalog generator 1
Catalog Clean
ai wholesale catalog generator 2
4:5 Line-sheet crop
ai wholesale catalog generator 3
Light grey seamless
ai wholesale catalog generator 4
C2PA-signed output

Browse 150+ visual styles →

Comparison

RAWSHOT vs category tools vs DIY prompting

Three lenses on every dimension — what you optimize for in RAWSHOT versus typical category tools and blank-box AI workflows.

  1. 01

    Interface

    RAWSHOT

    Click-driven controls for every shot decision—no text field required.

    Category tools + DIY

    Shorter controls, less direct art direction, and more guessing. DIY prompting: Typed prompt workflows that require managing wording and re-tries.
  2. 02

    Garment fidelity

    RAWSHOT

    Garment-led generation keeps cut, colour, pattern, logo, and drape faithful.

    Category tools + DIY

    Less garment fidelity; product details can drift between outputs. DIY prompting: Garment drift is common when the model interprets your wording instead of the garment.
  3. 03

    Model consistency across SKUs

    RAWSHOT

    Same face and body reused across your catalog to prevent visual drift.

    Category tools + DIY

    Model identity can change across variants, harming catalog uniformity. DIY prompting: Inconsistent faces across outputs create manual cleanup work.
  4. 04

    Provenance + labelling

    RAWSHOT

    C2PA-signed, watermarked, and AI-labelled with a signed audit trail.

    Category tools + DIY

    No consistent provenance story or publishing-ready labelling. DIY prompting: Missing provenance metadata makes it harder to support compliance workflows.
  5. 05

    Commercial rights

    RAWSHOT

    Full commercial rights to every output, permanent and worldwide.

    Category tools + DIY

    Rights framing is often unclear or not catalog-team friendly. DIY prompting: Unclear rights can slow publishing and licensing decisions.
  6. 06

    Iteration speed per variant

    RAWSHOT

    Generate predictable variants from stable settings in the same interface.

    Category tools + DIY

    Controls can be shallow, forcing more iteration for comparable results. DIY prompting: Prompt-engineering overhead costs time before you even reach a usable image.
  7. 07

    Catalog API

    RAWSHOT

    REST API supports batch production for catalog-scale pipelines.

    Category tools + DIY

    Often lacks a dependable catalog pipeline model and stable outputs. DIY prompting: DIY scripting around prompt re-generation is operationally heavy.
  8. 08

    Pricing transparency

    RAWSHOT

    Flat per-image pricing with token refunds on failed generations.

    Category tools + DIY

    Per-seat pricing and volume tiers that punish growth. DIY prompting: Variable token and retry costs tied to prompt success rates.

Prompting does not scale

Stop writing essays. Direct the shoot.

Most AI photo tools start with a blank text box. Rawshot turns the shoot into repeatable controls, so creative teams can produce consistent fashion imagery without prompt syntax or one-off hacks.

Category norm

Manual
Prompt box

Create a premium editorial fashion photograph of a model wearing the exact navy oversized wool coat from SKU-1842, full-body crop, realistic hands, consistent facial identity, clean e-commerce lighting, subtle Paris street background, 85mm lens, no logo distortion, no fabric hallucination, same pose as last campaign, repeatable for all colorways...

Needs prompt engineering
Breaks across SKUs
Hard to repeat

A prompt can describe one image. It cannot become a shared production system for hundreds of products, models, angles and markets.

Rawshot

Clicks

Saved shoot recipe

Apply to 1 SKU or 10,000 via GUI, CSV or REST API.

Scale
Preset-driven shoots anyone can repeat
Same model, pose and styling across a catalog
GUI for teams, API for production volume

Rawshot makes creative direction visible: buttons, presets and sliders instead of hidden prompt craft. The result is easier to teach, faster to approve and built for repeat production.

Use cases

From SKU sets to publish-ready line sheets

Operator archetypes and how click-directed, garment-first output fits the way they actually work.

  1. 01

    Catalog team at a DTC brand

    Generate consistent PDP and line-sheet images per SKU for wholesale distribution without reshoots.

    Confidence · high

  2. 02

    Indie designer launching a new drop

    Create campaign-grade line-sheet visuals with the same model setup across every colourway.

    Confidence · high

  3. 03

    Marketplace seller with many variants

    Batch-generate images that keep the garment faithful while maintaining a consistent face across listings.

    Confidence · high

  4. 04

    Factory-direct manufacturer

    Produce distributor-ready images for seasonal updates using stable settings and per-SKU generation.

    Confidence · high

  5. 05

    Resale and vintage curator

    Build clean catalog pages that present garments clearly while avoiding invented branding details.

    Confidence · high

  6. 06

    Student or design studio workflow

    Iterate quickly on styling and visuals with click-driven presets for portfolio-ready catalog outputs.

    Confidence · high

  7. 07

    Lingerie DTC for wholesale packs

    Generate consistent on-model imagery across SKUs so retailers can order with confidence in product presentation.

    Confidence · high

  8. 08

    Adaptive fashion line operator

    Create labelled, consistent catalog imagery for multiple product families without shipping samples.

    Confidence · high

  9. 09

    Footwear and accessory catalog maintainer

    Generate accessory-focused compositions with controlled framing for wholesale line sheets.

    Confidence · high

  10. 10

    Kidswear brand scaling SKUs

    Keep catalog uniformity while expanding size and colour variants using the same model setup.

    Confidence · high

  11. 11

    Adaptive retailer content operations

    Publish product-led visuals quickly with provenance metadata for internal review and brand governance.

    Confidence · high

  12. 12

    Wholesale distributor imaging intake

    Standardize incoming SKU imagery for seasonal catalog updates using a consistent, auditable output workflow.

    Confidence · high

— Principle

Honest is better than perfect.

RAWSHOT keeps provenance and publishing signals built in: C2PA-signed records, visible and cryptographic watermarking, and AI labelling. For catalog workflows, that means your team can document origin and processing with an auditable trail instead of relying on guesswork.

RAWSHOT · Editorial

Rights & provenance

Full commercial rights. Forever.

  • C2PA-signed on every image — EU AI Act Article 50 compliant
  • 28-attribute synthetic models — real-person likeness statistically impossible
  • Full commercial rights to every generation — no recurring licensing fees
  • Tokens never expire · One-click cancel · Transparent pricing

EU AI Act

C2PA

Commercial use

Pricing

~$0.55 per image.

~30–40 seconds per generation. Tokens never expire. Cancel in one click.

  • 01The cancel button is on the pricing page.
  • 02No per-seat gates. No 'contact sales' walls for core features.
  • 03Failed generations refund their tokens.
  • 04Full commercial rights to every output, permanent, worldwide.

FAQ

Practical answers on control, rights, pricing, scale, and compliant publishing.

Do I need to write prompts to use RAWSHOT?

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.

What does an AI-assisted fashion photo workflow change for wholesale catalogs?

You stop treating photography like a one-off production event. With RAWSHOT, you generate on-model imagery per SKU using stable controls for camera, framing, lighting, and visual style—so your catalog keeps a coherent look across releases.

Instead of re-shooting for every variant, you keep the garment as the brief and generate series-ready imagery with consistent models, C2PA-signed provenance, and full commercial rights. Use the REST API when you need batch speed, or the browser GUI when you’re dialing in a new line-sheet direction.

Why avoid DIY prompting when building a product line sheet for retailers?

DIY prompting often forces you to debug outputs rather than design with your garment. Generic models can drift on cut, colour, pattern, or logo placement, and they can shift the face and pose between images—so your catalog looks inconsistent even when you repeat a similar prompt.

RAWSHOT keeps creative choices inside the application controls, with garment-led fidelity and SKU consistency from a saved synthetic model. Every output also ships with provenance and auditability, which makes it easier for commerce teams to review and publish with confidence.

How do we turn flat garments into catalogue-ready imagery without prompt text?

In RAWSHOT, you direct the shoot with UI controls: pick lens and framing, set the lighting and background, choose a visual style preset, and select a pose. The garment stays the brief, so the product details read correctly in the final output.

For catalog work, you’ll usually standardize the framing and lighting first, then iterate only what changes between SKUs. Generate the series quickly, keep the same model setup across variants, and publish outputs with C2PA-signed provenance and watermarking cues.

How does click-driven fashion control compare to ChatGPT or Midjourney for PDP imagery?

Chat-style workflows turn your intent into wording and ask a model to interpret it, which creates unpredictable variation between outputs. That’s especially painful for product pages where you need the same face and consistent garment presentation across dozens or hundreds of SKUs.

RAWSHOT is built as a fashion application: lens, angle, frame, lighting, background, and style are buttons and presets. You also get SKU consistency by saving a model, and you receive C2PA-signed provenance, watermarking, and per-image audit trail along with full commercial rights.

Can we use RAWSHOT outputs commercially for wholesale marketing and retailer decks?

Yes. RAWSHOT provides full commercial rights to every output, permanent and worldwide, so catalog teams can license images for wholesale marketing and retailer presentations without extra legal ambiguity.

On top of rights, outputs are C2PA-signed and labelled with visible and cryptographic watermarking plus a signed audit trail. That combination is designed for publish-ready governance, so your team can review before delivery with an auditable record.

What provenance and compliance signals come with RAWSHOT images?

Each output includes C2PA-signed provenance metadata, visible and cryptographic watermarking, and AI labelling. You also receive a signed audit trail per image so your internal review process can document origin and processing steps.

For teams operating under compliance expectations, these signals are included in the output workflow rather than added later. That keeps your catalog pipeline consistent from batch generation through publishing.

How do the token and generation timings work for catalog-scale image production?

For photos, pricing is per image at about ~$0.55 per image, with generation around ~30–40 seconds per generation. Tokens never expire, and failed generations refund tokens so you’re not paying for retries that don’t produce usable outputs.

You can also cancel in one click from the pricing page, which helps keep production runs controlled. If you need to refresh a collection quickly, batch generation plus stable settings can reduce the operational overhead compared to re-running entire shoots.

Do we need a REST API to run a catalog pipeline, or can teams operate inside the browser GUI?

You can do either. RAWSHOT supports a browser GUI for single shoots and a REST API for catalog-scale pipelines, both using the same garment-led controls for shot setup.

If you’re iterating on a line-sheet direction, the GUI is fast for approvals. If you’re producing thousands of SKUs nightly, the REST API lets your commerce workflow batch generation while keeping SKU consistency and provenance signals intact across outputs.

What’s the best way to keep faces and styling consistent across an entire wholesale catalog?

Use a saved model and standardize the shot controls that define your catalog look—framing, lighting, background, and visual style. That way, new SKUs generate against the same synthetic model setup, so you avoid drift between images.

In practice, teams set a base style for the catalog line sheet, then change only the garment and any composition details that truly vary by SKU. You get stable results plus C2PA-signed provenance, watermarking, audit trails, and full commercial rights for publishing workflows.