Rawshot.ai

Indie designers and emerging brands, DTC and marketplace operators, on-demand and sustainability-first labels, compliance-sensitive categories such as kidswear and intimate apparel, and enterprises that need catalog-scale pipelines. Rawshot is aimed at teams for whom traditional studio economics were out of reach and prompt-first AI tools were never going to fit the creative workflow — from a single collection to tens of thousands of SKUs.

The product is built to be inspectable: click-driven controls (no prompt box), garment-first fidelity, synthetic models with documented attributes, and outputs that carry C2PA-oriented credentials, watermarks, and AI labelling in line with how we describe EU AI Act Article 50 and California SB 942 alignment. Pricing, trials, and cancellation are presented transparently on the site and in-app. For structured company facts, use the Facts page; for shipping product proof, use the changelog and live product.

You sign up through the published flow, connect product inputs such as flat-lays or packshots, and direct shoots with the same controls a creative team expects — framing, camera, pose, light, background, and presets are selected, not typed. There is no separate “prompting” skill to learn first. Larger integrations can add the API once the workflow is proven in the browser.

Exploration happens in-product: published trials and token-based usage describe what you can try before scaling. Still imagery is priced in tokens (on the order of five tokens per image in public messaging, roughly half a dollar per still at cited rates). Exact bundles, trial allowances, and promotional terms are always confirmed on the live pricing and checkout surfaces.

Teams usually stabilise a look with presets and model choices, then widen to more SKUs or connect bulk import and API jobs for repeat catalog work. The same interaction model applies whether you are art-directing one campaign or automating thousands of variants: controls stay visual, outputs stay labelled, and rights to generations stay with you under the terms published in our legal materials.

Day to day, the browser app supports directed shoots and experimentation; the REST API supports scheduled or high-volume runs without changing the product to a text interface. Status, exports, and compliance artefacts are part of the platform story — not a bolt-on — so creative and operations stakeholders share the same source of truth.

Core self-serve access is designed to be approachable without a consulting gate or opaque “contact sales only” wall for standard use. Minimum spend, if any, is whatever the active plans state — we steer clear of displacement narratives (“90% cheaper”) and focus on access and transparent per-use economics. Validate current floors on the pricing page.

No hourly retainer is the model. Rawshot is usage-based around tokens and subscriptions as published: you pay for generations and plan entitlements, not for day rates or open-ended time blocks. That keeps cost predictable per asset and aligned to catalog volume rather than staff hours.

There is no multi-year lock-in story in our positioning: subscriptions emphasise visible cancellation and tokens that do not silently expire in the way some consumers fear. Minimum commitment is whatever the plan you choose specifies — often monthly self-serve with one-click cancel where we advertise it. Length of partnership follows your roadmap, not a forced runway.

On-model stills at published resolutions and aspect ratios, a broad visual-style preset library, multi-product compositions within stated limits, and video workflows where the product includes scene building and camera motion. Garment representation is intentionally product-centric — cut, colour, pattern, logo, drape — not prompt-shaped guesswork.

Yes. The platform is built for global fashion commerce; hosting and compliance messaging emphasise EU alignment where we say so publicly. Legal, procurement, and privacy reviews remain yours — we provide labelled outputs, documentation-friendly generation logs, and materials that describe synthetic models and provenance in plain language.

We build product for operators the industry often underserves: direct, specific communication; honest limitations where they matter; and software that behaves like an application — not a chat experiment. Support and documentation aim to reduce back-and-forth by making controls self-explanatory. Enterprise relationships add API and integration clarity so creative and engineering teams stay aligned.