— On-model imagery · 150+ styles · 4K-ready
Direct campaign-ready fashion imagery, directed by clicks — with the AI Relaxed Poses Generator.
Generate catalog-true poses on real garments with a click-driven interface, not a text field. Adjust camera, framing, pose, mood, and background in the browser, then produce 2K or 4K stills. No studio booking. No sample shipping. No prompts.
- ~$0.55 per image
- ~30–40 seconds per generation
- 150+ visual styles
- 2K and 4K
- GUI + REST API
- Full commercial rights
7-day free trial • 50 tokens (10 images) • Cancel anytime


Direct the shoot. Zero prompts.
Your garment stays the brief. RAWSHOT locks the model posing workflow to relaxed, browser-directable controls—then renders 2K/4K stills with C2PA-signed provenance and watermarking. 5 tokens · ~34s per image
- 6 clicks · 0 keystrokes
- app.rawshot.ai / new_shoot
How it works
Click a relaxed pose, then publish labelled stills
A browser GUI for on-model shoots with 2K/4K exports, plus REST batch support for SKU-scale pipelines—without prompt entry.
- Step 01
Select garment-first controls
Upload the garment, then choose lens, framing, pose, angle, lighting, and background from fixed presets. Every setting is a click, with no text entry required.
- Step 02
Dial the relaxed look
Refine the mood and visual style to match your campaign or catalogue—keeping the garment cut and markings faithful. Generate consistent stills in 2K or 4K for your chosen aspect ratio.
- Step 03
Label, watermark, publish
Outputs include C2PA-signed provenance, visible and cryptographic watermarking, and AI labelling. Download and ship to PDP, lookbook, or marketplace workflows with full commercial rights.
Spec sheet
Proof that relaxed posing stays on-brief
Twelve proof surfaces confirm the controls, garment fidelity, model consistency, labelled provenance, and catalog-scale delivery for your posing sets.
- 01
No-likeness by design
RAWSHOT builds synthetic models 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, no prompting
Camera, angle, distance, framing, pose, facial expression, light, background, and product focus are buttons and sliders. You direct the shoot with controls, not text.
- 03
Garment fidelity you can rely on
Cut, colour, pattern, logo, fabric, and drape are represented faithfully. Where generic generators drift around a text request, RAWSHOT stays garment-led.
- 04
Synthetic models, transparently labelled
Diverse synthetic models are used across styles and shoots. Outputs carry AI labelling so teams can publish with clarity, not ambiguity.
- 05
SKU consistency across your catalog
Same model face and body persist across your SKUs, preventing drift between variants. One pose direction stays coherent across your entire catalogue run.
- 06
150+ visual styles for every mood
Switch between catalog, lifestyle, editorial, campaign, studio, street, Y2K, vintage, noir, and more. Your relaxed posing set can match each collection’s visual language.
- 07
2K/4K and every aspect ratio
Generate high-resolution stills in 2K or 4K with any aspect ratio you need. Create full-body, half-body, close-up, detail, and flat-lay framings.
- 08
Compliance built into the output
C2PA-signed provenance, EU AI Act Article 50 compliance, and California SB 942 compliance. This is part of how the platform produces trustworthy fashion imagery.
- 09
Signed audit trail per image
Each output includes a signed audit trail that records production context. Teams get accountability for creative approvals and internal publishing workflows.
- 10
GUI for singles, REST API for scale
Use the browser GUI for on-demand shoots, then switch to REST for catalogue pipelines. Same engine, same controls, and the same image quality.
- 11
Fast generation with predictable pricing
~$0.55 per image at ~30–40 seconds per generation, with tokens that never expire. Failed generations refund tokens, so production stays controlled.
- 12
Full commercial rights, permanent, worldwide
Every output includes full commercial rights—permanent and worldwide. Publish for ecommerce, marketplaces, and campaigns without an unclear rights story.
Outputs
Relaxed pose sets, ready for commerce Garment-led, labelled, and consistent
Browse a small set of sample outputs that show relaxed posing controls, garment fidelity, and publishing-ready provenance. Use them as a visual baseline for your next collection.




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, framing, pose, light, and style.Category tools + DIY
Shorter controls and fewer pose/lighting parameters. DIY prompting: Typed prompts and control-by-guessing through a chatbot-style UI.02
Garment fidelity
RAWSHOT
Cut, colour, pattern, logo, and drape stay garment-true.Category tools + DIY
More variation around product details under paraphrased intent. DIY prompting: Garment drift and unintended redesign from prompt phrasing.03
Model consistency across SKUs
RAWSHOT
Same model face and body persist across your catalogue set.Category tools + DIY
Faces and proportions can shift between variants. DIY prompting: Inconsistent faces across outputs, making catalog consistency hard.04
Provenance + labelling
RAWSHOT
C2PA-signed provenance with visible plus cryptographic watermarking.Category tools + DIY
Often lacks clean provenance and AI labelling workflows. DIY prompting: Missing provenance metadata and unclear watermarking behaviour.05
Commercial rights
RAWSHOT
Full commercial rights to every output, permanent and worldwide.Category tools + DIY
Licensing can be unclear or tied to usage tiers. DIY prompting: Unclear rights story when outputs are generated outside a dedicated product workflow.06
Iteration speed per variant
RAWSHOT
Generate relaxed pose sets quickly with stable garment mapping.Category tools + DIY
Iteration can require multiple attempts to regain product accuracy. DIY prompting: Iteration loops depend on prompt rewrites and guesswork.07
Pricing transparency
RAWSHOT
~$0.55 per image with ~30–40 seconds per generation and token refunds.Category tools + DIY
Per-seat pricing or volume tiers that complicate budgeting. DIY prompting: Hidden costs via tokens and variable compute across attempts.08
Catalog API
RAWSHOT
GUI for singles and REST API for batch catalogue pipelines.Category tools + DIY
Limited pipeline support or fragmented export formats. DIY prompting: Automation is manual and brittle when outputs vary per request.
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
From relaxed looks to full catalog sets
Operator archetypes and how click-directed, garment-first output fits the way they actually work.
- 01
Indie designer launching a collection
You select a relaxed pose preset, keep your garment cut intact, and generate ecommerce-ready stills without booking studio days.
Confidence · high
- 02
DTC brand refreshing season updates
You reuse the same model and pose direction across SKUs, keeping product details stable while pushing new imagery faster.
Confidence · high
- 03
On-demand label shipping capsule drops
You generate relaxed lookbook-style frames per outfit and publish with labelled provenance and permanent commercial rights.
Confidence · high
- 04
Crowdfunding creator building a reward catalogue
You create consistent on-model imagery for backer updates, with an audit trail that supports internal approvals.
Confidence · high
- 05
Kidswear operator scaling multiple fits
You generate relaxed poses with consistent styling across variants, then output in the aspect ratios marketplaces require.
Confidence · high
- 06
Adaptive fashion line producing inclusive catalogue imagery
You direct relaxed posing with garment-first controls and ensure outputs carry AI labelling and watermarking for trust.
Confidence · high
- 07
Lingerie DTC maintaining brand-safe presentation
You choose catalog clean and campaign gloss styles, generate 2K/4K stills, and keep garment fidelity consistent across the set.
Confidence · high
- 08
Resale and vintage seller building marketplace listings
You turn each garment into on-model catalogue frames quickly, with clear provenance signalling for every image.
Confidence · high
- 09
Marketplace seller standardizing product cards
You keep a single relaxed posing direction across inventory so customer-facing pages feel cohesive and consistent.
Confidence · high
- 10
Factory-direct manufacturer producing seasonal PDP refreshes
You batch-generate SKU photography via REST API while keeping model consistency and garment representation on brief.
Confidence · high
- 11
Makers and students building a portfolio
You explore relaxed poses with 150+ visual styles and export labelled outputs for critique and publishing.
Confidence · high
- 12
Catalog team running nightly SKU pipelines
You use the same relaxed pose workflow for thousands of images, with predictable pricing, audit trails, and stable model behaviour.
Confidence · high
— Principle
Honest is better than perfect.
RAWSHOT outputs include C2PA-signed provenance and watermarking, plus AI labelling for publishing clarity. This matters for relaxed posing sets because teams need a reliable, auditable record alongside consistent garment-led imagery—so approval and compliance workflows stay simple.
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 garment inventions.
What does a click-driven relaxed-posing workflow change for ecommerce SKUs?
A click-driven workflow turns “pose decisions” into repeatable controls, so your relaxed looks stay coherent across variants. Instead of chasing accidental outcomes, you select pose, framing, lighting, and mood as fixed settings and generate stills in 2K or 4K.
For SKU work, that matters because stable garment representation and consistent model behaviour reduce retakes and approval churn. You can generate a full set in the browser for single drops, then move to REST for the catalogue pipeline.
Why do teams skip reshooting every SKU when they launch a season update?
Reshooting is slow, expensive, and operationally heavy when the season update changes only styling or colour. With RAWSHOT, you preserve the garment as the brief and generate on-model imagery sets quickly without studio days or sample shipping delays.
You still keep the proof surfaces that publishing teams need: C2PA-signed provenance, visible and cryptographic watermarking, and an audit trail per image. That makes approvals smoother because the output carries the documentation your workflow expects.
How do we turn a flat garment into catalogue-ready relaxed posing imagery without text instructions?
You start by uploading the garment and then select the creative intent with controls: framing, pose choice, camera angle, lighting system, background, and visual style. The platform renders on-model stills where cut, colour, pattern, logo, and drape remain faithful to your product.
After you generate, you download labelled outputs with permanent commercial rights for PDPs, marketplace cards, and campaign usage. If you need more variants, you reuse the same pose direction rather than rewriting any creative instructions.
How does garment-led control beat prompt roulette for fashion PDPs?
Prompt roulette happens when small wording changes produce different garments, different faces, and different results across outputs. RAWSHOT is engineered around the garment—so the creative direction you click maps to stable production controls rather than an unpredictable text field.
That stability is exactly what catalogue teams need when they publish the same product across hundreds of SKUs and aspect ratios. You also get provenance and labelling that reduce review friction for compliance-minded buyers.
What trust details are included in RAWSHOT outputs for publishing?
Every output includes C2PA-signed provenance, plus visible and cryptographic watermarking and AI labelling. You also receive a signed audit trail per image, which helps teams keep decisions accountable during approvals and production cycles.
For relaxed posing imagery, these trust details matter because teams need consistent, labelled outputs they can publish with confidence. It’s not just about aesthetics; it’s about what the image claims and how it’s documented.
Before we publish, what QA checks should we run on relaxed pose sets?
Run a fast QA pass for garment fidelity, framing match, and SKU consistency before you publish. Confirm that logos and patterns read correctly, that the pose and mood match your campaign or catalogue intent, and that the selected aspect ratios match the placement requirements.
Then verify publishing proof: C2PA provenance, watermarking presence, and labelling cues on the download. With those checks in place, approvals become repeatable instead of subjective retakes.
How do token costs work for still image relaxed posing, and what happens on failed generations?
For photos, pricing is ~0.55 USD per image with around 30–40 seconds per generation, and tokens never expire. If a generation fails, RAWSHOT refunds the tokens so production stays predictable.
That cost structure is useful for commerce teams who iterate through variants—pose, lighting, and style—without fear of burning budget on unpredictable outcomes. You can also cancel in one click from the pricing page when you stop a run.
Can we integrate relaxed pose generation into a catalog pipeline with REST API?
Yes. RAWSHOT supports REST API for catalogue-scale workflows while the browser GUI covers single-shoot work. That means you can keep the same relaxed posing controls across batch runs for PDP refreshes and nightly SKU updates.
Because the platform’s interface-to-output mapping is consistent, your pipeline can reproduce the same creative direction without manual intervention. The outputs include the provenance and watermarking signals that downstream publishing teams need.
For a team producing thousands of product images, how do roles and workflow stay manageable?
Designers can direct relaxed posing with the same controls in the browser, while production teams run batch jobs through the REST API for catalog scale. Approvers focus on garment fidelity and framing checks instead of prompt debugging or inconsistent creative outcomes.
Operationally, you get predictable per-image pricing, refund handling for failed generations, and labelled provenance on every file. That combination keeps roles clear: creative sets the direction, operations scales it, approvals verify it.
Keep exploring