Veesual is an AI-driven visual commerce platform focused on fashion e-commerce. The product creates on-model visuals, outfit “shop the look” experiences, mix-and-match real-time outfit builders, multi-size/multi-model renderings and augmented clienteling imagery to boost engagement, average order value (AOV) and conversions while helping reduce returns. Core use cases called out on the site include Virtual Styling (look inspiration), Mix&Match (real-time outfit builder), Virtual Fitting (size/fit tools with Switch Model / multi-sizing), Augmented Clienteling for luxury stores, and conventional VTO/AR for simpler categories. Key features and technical claims: on-model look inspirations (full outfits on models or AI mannequins), smart merchandising rules, mobile-first responsive UI; Mix&Match real-time outfit builder with multiple angles and add-to-cart support via JS integration; Switch Model / Multi-Sizing to render the same garment on multiple digital models/sizes; HD renderings and post-purchase activations for augmented clienteling; image generation that relies on brand inputs (garment packshots, front/back shots, and sizing data) to preserve drape, lighting, texture and relative sizing; and integrations via a JavaScript widget plus product feed/CMS/e-commerce platform connectivity. The site positions KPI benefits such as increased pages/session and time on site, higher conversion rates, higher AOV, and reduced returns. Typical implementation timelines published on the site: Look Inspiration estimated 6–8 weeks from model selection and packshot submission to launch; Mix&Match core features advertised at ~4 weeks for essential features; Augmented Clienteling described as an ~8-week plan for luxury implementations. Typical requirements include casting/selecting models (or choosing AI mannequins), brand packshots (front/back/underwear), connection to product feed/CMS, and sizing data. No public pricing or self-serve plans were found: the site’s /pricing URL returns a 404 and automated extraction found no published plans, no free trial listing, and no per-seat or self-serve plans; pricing appears to be enterprise / custom and requires contacting Veesual for a quote. Contact information and channels found on the site: [email protected] (listed on a blog post about Mix&Match) and [email protected] (listed in the Privacy Policy for privacy/data questions). Other contact methods include requesting a demo or contact via the homepage and the company LinkedIn (linkedin.com/company/veesual). Notable partnerships and press mentions listed include Eileen Fisher (multi-model digital representation) and press coverage about funding and product updates; the company raised a $7.5M seed round according to press coverage linked from the site. Resources available on the site include an AI Styling Playbook 2025, multiple blog posts explaining VTO/Virtual Fitting/Virtual Styling, solution pages for Mix&Match and Look Inspiration, and a Press & Media page. Privacy and legal: the Privacy Policy (site /legals) describes personal and non-personal data collection, cookie usage, third-party analytics, transfers to France, retention periods, and user rights (access, rectification, deletion, portability); privacy contact listed as [email protected]. The site also hosts Terms & Conditions at /terms-and-conditions. Next suggested actions (as noted): email [email protected] or use the demo/contact form requesting pricing and a tailored implementation plan (include expected catalog size, sample garment packshots, target markets, and tech stack), ask for case studies and concrete KPI benchmarks for similar brands, request an integration checklist (file formats, feed spec, JS snippet, data security/hosting), and request data handling and security/processing agreement details if privacy is a concern.