— On-model imagery · 150+ styles · 2K/4K
Direct campaign-ready fashion imagery, with the Mittens AI On-model Photography Generator behind every click.
You get studio-quality on-model results for real garments, not generic mockups. Select lens, framing, light, and visual style in the RAWSHOT interface—every setting is a control, not a text field. No studio days. No samples. No prompts.
- ~$0.55 per image
- ~30–40s per generation
- 2K or 4K
- 150+ visual styles
- Catalog-ready aspect ratios
- Full commercial rights, permanent worldwide
7-day free trial • 50 tokens (10 images) • Cancel anytime


Direct the shoot. Zero prompts.
Every creative decision is a selection: lens, framing, pose, lighting, background, mood, and a visual style preset. The garment stays faithful while you generate on-model shots for your next catalog or campaign drop. 5 tokens · ~34s per image
- 6 clicks · 0 keystrokes
- app.rawshot.ai / new_shoot
How it works
Click-driven shoots, garment-faithful output
Direct your next on-model set with presets and controls. No prompts—just camera, light, framing, and visual style choices that stay consistent.
- Step 01
Set the garment-led controls
Click lens, framing, pose, lighting, background, and a visual style preset. You direct the shoot without typing anything into a text box.
- Step 02
Generate on-model imagery in seconds
Start the generation and review results as they render in your workspace. Tokens are priced per generation, and failed generations refund tokens.
- Step 03
Publish with signed provenance
Every output is C2PA-signed, watermarked, and AI-labelled. You also get an audit trail per image so teams can ship confidently at catalog scale.
Spec sheet
Proof that matches real product photography
Twelve proof surfaces that cover UI control, garment fidelity, synthetic model labelling, compliance, and catalog-scale delivery—from browser to REST API.
- 01
No-likeness by design
RAWSHOT uses synthetic models built from 28 body attributes with 10+ options each. Accidental real-person likeness is statistically negligible by design, and every output is transparently labelled.
- 02
Click-driven UI, zero prompts
Every creative decision is a button, slider, or preset—camera, angle, distance, frame, pose, facial expression, and more. There’s no prompt box to learn or babysit.
- 03
Garment fidelity stays locked
Your garment is the brief. Cut, colour, pattern, logo, fabric, and drape are represented faithfully so your PDP and lookbook images match the actual product.
- 04
Diverse synthetic models
Choose from diverse synthetic models while keeping them transparently labelled. Your imagery can represent a broader customer range without reliance on likeness risk.
- 05
SKU consistency across catalog
Use the same model and face across your SKUs to avoid drift between shoots. The result: consistent on-model storytelling without retakes for every variant.
- 06
150+ visual styles
Switch between catalog, lifestyle, editorial, campaign, studio, street, Y2K, vintage, noir, and more. Style changes stay coherent so your brand kit feels repeatable.
- 07
2K/4K and every aspect ratio
Generate at 2K or 4K and choose your aspect ratio for your platform destinations. Full-body, half-body, close-up, detail, and flat-lay framings are covered.
- 08
Compliance and labelling included
Outputs are C2PA-signed with visible and cryptographic watermarking. RAWSHOT is designed to be EU AI Act Article 50 compliant (effective 2 Aug 2026) and California SB 942 compliant.
- 09
Per-image signed audit trail
Each output includes signed provenance metadata and an audit trail per image. Your teams can verify what was generated and when—without guessing.
- 10
GUI for shoots, REST API for scale
Run single-shoot work in the browser GUI, or plug catalog pipelines into the REST API. Same engine, same quality, no separate workflow to manage.
- 11
Pricing you can operate daily
Photo generation is priced per image at ~$0.55 with ~30–40 seconds per generation. Tokens never expire, and failed generations refund tokens.
- 12
Full commercial rights, worldwide
You receive full commercial rights to every output, permanent and worldwide. Use your generated imagery across channels without rights ambiguity.
Outputs
Turn your next drop into a consistent on-model set One interface, per-image control
Preview how RAWSHOT renders product-led on-model imagery with signed provenance, watermarking, and catalog-ready formatting.




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.
01
Interface
RAWSHOT
Click-driven controls for camera, light, framing, pose, and style.Category tools + DIY
Controls are shorter and less specific, often requiring prompts. DIY prompting: You type descriptions and fight unclear controls to get usable outputs.02
Garment fidelity
RAWSHOT
Garment-led generation keeps cut, colour, pattern, logo, and drape faithful.Category tools + DIY
Garments can drift, with weaker product representation over variations. DIY prompting: DIY models often mutate the product across iterations and angles.03
Model consistency across SKUs
RAWSHOT
Reuse the same model and face across your entire catalog, avoiding drift.Category tools + DIY
Faces and bodies may change between generations, breaking SKU storytelling. DIY prompting: Inconsistent faces are common when you rerun prompts per product variant.04
Provenance + labelling
RAWSHOT
C2PA-signed, visible + cryptographic watermarking, and AI-labelled outputs.Category tools + DIY
Often lacks clean provenance and consistent labelling for compliance. DIY prompting: DIY outputs rarely include audit-ready metadata or signed provenance.05
Commercial rights
RAWSHOT
Full commercial rights to every output, permanent and worldwide.Category tools + DIY
Rights narratives are unclear or tied to tooling terms rather than outputs. DIY prompting: DIY usage can leave teams uncertain about licensing and publishing readiness.06
Iteration speed per variant
RAWSHOT
~30–40 seconds per image with operational pricing and refund handling.Category tools + DIY
Iteration can be slower or less repeatable due to control gaps. DIY prompting: Iteration adds overhead: you re-prompt, re-tune, and often redo variants.07
Pricing transparency
RAWSHOT
Per-image pricing with tokens that never expire and one-click cancel.Category tools + DIY
Per-seat gates and volume tiers can punish growth and slow teams down. DIY prompting: Token and compute costs stack unpredictably while you iterate prompts.08
Catalog API
RAWSHOT
GUI for single shoots and REST API for catalog-scale pipelines.Category tools + DIY
Automation paths are limited or require separate integrations and workarounds. DIY prompting: DIY workflows don’t provide a stable, batch-ready garment-led pipeline.
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
ManualCreate 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...
A prompt can describe one image. It cannot become a shared production system for hundreds of products, models, angles and markets.
Rawshot
ClicksSaved shoot recipe
Apply to 1 SKU or 10,000 via GUI, CSV or REST API.
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
Catalog and campaign teams at brand scale
Operator archetypes and how click-directed, garment-first output fits the way they actually work.
- 01
Indie designer on a tight launch window
Generate brand-consistent on-model imagery for lookbooks and PDP previews without scheduling studio time.
Confidence · high
- 02
DTC brand refreshing seasonal colorways
Update existing SKUs with the same model and face so customers see the new garment truthfully, not a drifted copy.
Confidence · high
- 03
Crowdfunding creator shipping visuals on demand
Spin up campaign-ready shots quickly when pledges unlock new variants, keeping visuals consistent across updates.
Confidence · high
- 04
Kidswear label with repeatable product framing
Produce on-model imagery across close-ups and half-body framings while maintaining garment cut and pattern fidelity.
Confidence · high
- 05
Adaptive fashion line with transparent on-model sets
Generate catalogue-ready imagery with diverse synthetic models while keeping every output labelled and provenance-traceable.
Confidence · high
- 06
Lingerie DTC building channel-ready PDP assets
Use visual style presets and controlled lighting to keep brand aesthetics stable across every SKU.
Confidence · high
- 07
Resale and vintage marketplace seller
Create product-led on-model views for listings without waiting for new studio sessions per item category.
Confidence · high
- 08
Factory-direct manufacturer preparing wholesale assortments
Batch-produce imagery across many garments with GUI for review and REST API for production flow.
Confidence · high
- 09
Makers and pattern teams documenting detail shots
Generate detail, close-up, and flat-lay-like framings that emphasize fabric, logo, and pattern accuracy.
Confidence · high
- 10
Student studio workflow without studio budgets
Learn fashion imaging fundamentals using click-driven camera and lighting controls—then export imagery for assignments with signed provenance.
Confidence · high
- 11
Influencer brand kit for consistent storefront visuals
Keep your on-model face and style direction aligned across platforms by generating from the same controls.
Confidence · high
- 12
10,000-SKU catalog refresh pipeline
Run nightly generation via REST API while preserving SKU consistency, watermarking, and full commercial rights for every output.
Confidence · high
— Principle
Honest is better than perfect.
RAWSHOT outputs carry signed provenance and AI-labelling with visible plus cryptographic watermarking. That’s not a checkbox; it’s brand equity. Teams can publish with clearer compliance posture while operators direct the garment-led creative choices through the UI.
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.
In practice, you pick lens and framing, select lighting and background, then choose a visual style preset. When you start a generation, you’re not guessing how an LLM will interpret your text; you’re directing a fashion application with garment-led controls that stay stable across variants.
What does on-model garment control change for a product catalog team?
It turns fashion imagery from a bespoke shoot into a controlled workflow. Instead of re-running improvisational outputs for each SKU, you click camera and style settings while keeping the garment faithful—cut, colour, pattern, logo, and drape. This matters when your storefront expects consistent visuals across PDPs, category pages, and seasonal refreshes.
RAWSHOT is engineered around the real product, so the garment is the brief. You can generate in the browser for review, then scale through the REST API for catalog pipelines with consistent results and the same provenance cues your compliance process expects.
Why skip reshooting every SKU for seasonal updates?
Because reshoots multiply cost, scheduling risk, and turnaround time. When you need imagery for new colours, materials, or bundles, you shouldn’t wait for studio availability and sample shipping across distances. A click-driven on-model workflow keeps your brand’s product story current without losing visual direction between updates.
With RAWSHOT, you reuse the same controls and generate new outputs per image price while maintaining garment fidelity and model consistency across SKUs. Every generation includes signed provenance and watermarking so you can publish confidently while your catalog refresh stays predictable.
How do we turn flat garments into catalogue-ready imagery without prompting?
You don’t translate a text idea into images; you direct the shoot through application controls. In RAWSHOT, you select framing (full body, half body, close-up, detail, flat-lay style), pose, camera angle, lighting, background, mood, and a visual style preset. The garment stays faithful because the engine is built around the real product details.
After you click Generate, you review results as on-model imagery rather than negotiating prompt interpretation. For faster iteration, you can adjust one control at a time—like switching lighting from studio softbox to window light—while preserving the rest of your creative direction.
How does RAWSHOT compare to ChatGPT or generic image generators for fashion PDPs?
RAWSHOT is designed around garment-led control and catalog repeatability, not prompt roulette. Generic tools often give shorter or weaker controls, and outputs can drift in garment appearance, face identity, or even branding. For product pages, that inconsistency forces your team into rework—extra edits, reshoots, or re-generations until it looks usable.
RAWSHOT keeps click-driven settings, supports browser GUI plus REST API for scale, and ships outputs with C2PA-signed provenance, watermarking, and clear commercial rights. The result is a workflow ecommerce teams can operate consistently across variants.
Will the AI output be labeled and have clean provenance for compliance reviews?
Yes. RAWSHOT outputs are C2PA-signed, include visible and cryptographic watermarking, and are AI-labelled so teams can handle review and publishing with more transparency. That provenance signalling is part of the output, not an after-the-fact add-on.
For operators, you also get a signed audit trail per image. This gives compliance-focused teams something they can verify, while creative teams stay focused on garment-led direction and consistent style choices.
What quality checks should we run before publishing on-model images?
Start with garment fidelity and identity consistency. Check that cut, colour, pattern, logo, and drape match the actual product, then verify your model face stays consistent across SKUs so your catalog doesn’t show drift between variants. Next, confirm the output is watermarked and carries the expected labelling and provenance cues.
Finally, validate formatting for your destinations: aspect ratio, resolution (2K or 4K), and framing (full body, half body, detail, and flat-lay-like setups). RAWSHOT’s signed provenance and per-image audit trail help you keep those checks operational instead of subjective.
What are the token and pricing basics for photo generation?
Photo generation is priced per image at about ~$0.55, with roughly 30–40 seconds per image generation. Tokens never expire, and failed generations refund tokens so your team isn’t punished for an occasional rerun. You can also cancel with one click from the pricing page.
This model matters when you need predictable daily output volume for product teams. You can plan around per-image cost and generation time, then keep production moving with refund handling rather than waiting for manual exceptions.
Can we integrate RAWSHOT into an existing catalog workflow with an API?
Yes. RAWSHOT supports a browser GUI for single shoots and a REST API for catalog-scale pipelines. That means creative direction stays consistent while your production workflow can remain batch-driven for large assortments.
For commerce teams, this reduces friction between departments: creatives review sets in the GUI, then catalogs generate at scale through API calls. Every output still carries signed provenance, watermarking, and AI-labelling so operational integrity doesn’t depend on manual packaging.
Will click-driven generation help us scale output across roles without extra prompt training?
That’s the point. RAWSHOT is built as a real application for fashion teams, so operators can click camera, lighting, framing, and visual style controls without learning prompt syntax. Different roles can work from the same controlled interface: creatives set direction, while production and catalog teams run batches with consistent settings.
When you pair that with signed provenance, per-image audit trail, and full commercial rights for every output, scaling becomes operational rather than chaotic. You can push throughput while keeping publish-ready outputs aligned with your brand standards.
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