Sprello is an AI product development and merchandising platform for fashion, beauty, and lifestyle brands. It connects AI-driven product creation, product data, collection reviews, line sheets, and buyer assortment, with the goal of helping teams move faster and reduce sampling waste.
In terms of purpose, it is officially positioned as a tool for going "from product concept to buyer-ready collection," enabling teams to move from the initial concept to commercial decisions. It emphasizes "one product record, from first sketch to buyer assortment," keeping visuals, product details, and assortment decisions connected.
Its main capabilities can be summarized in several stages. First, a shared product catalog: every style is stored in one place, including its details and the visual assets created for that style; selected visuals and product details flow into line sheets and buyer assortments; you can see which products already have approved visuals and which still need work; opening any product lets you find its sketches, materials, and all the options that were explored. Second, the canvas: bring sketches, CADs, materials, and references onto the canvas to explore visual directions with designers involved; every input and instruction remains visible on the canvas; changing one reference lets you compare results; workflows can be saved and run again on the next style. Third, collection review: compare visual options under the correct product record, gather feedback, and select the image to show. Fourth, line sheets and buyer assortment: pull selected visuals and details directly from the catalog without repeatedly copying images into slides; build separate assortment mixes for different buyers, clients, channels, or internal buying teams from the same product information; review the mix as a whole instead of rebuilding it somewhere else.
In terms of usage, the official description outlines a three-step process: catalog, canvas, line sheet and assortment. Line sheets can choose the display type (such as a wholesale line sheet), choose visible details (such as style/variant code, material, wholesale price, retail price), and more. Examples provided on the page include a handbag catalog, a product record for a drawstring bucket bag, colorway exploration (six colorways generated from one sketch), and assortments for North American department stores, European boutiques, and more.
In terms of use cases, the official list of best-fit categories includes: fashion and apparel (editorial campaigns for every SKU, colorway, and region), beauty and cosmetics (catalog-level depth of hero images, before-and-after comparisons, and ingredient stories), jewelry and accessories (on-demand detail-level product renders and lifestyle scenes), and home and lifestyle (room setups, seasonal updates, and style variations without reshoots).
In terms of enterprise capabilities, the official description states: SOC 2 compliance; role-based access control, giving the right people the right permissions over accounts and data; via identityprovider implementation of SSO/SAML single sign-on, so teams log in the way they already do and permissions follow the directory as people join or leave; zero training on data - designs, sketches, and uploaded content are not used to train its models or anyone else's models; encrypted storage and transmission, with strict data isolation between workspaces; dedicated onboarding and training (workflow setup, training sessions); a private Slack channel with 24/7 support from the founding team.
Regarding limitations, the official materials do not provide specific pricing, a free plan, platform form (web/desktop/mobile), supported export formats, or an integration list; these are not currently available.
