Lily AI
The semantic glue between product attributes and consumer search intent for enterprise retail.
Transform flat-lay photography into hyper-realistic on-model studio shots in seconds.
FashionAI by Sharp (sharp.ai) represents the 2026 frontier of neural rendering and diffusion-based image synthesis tailored specifically for the global apparel industry. The platform utilizes proprietary 'Cloth-Preserving GANs' and Latent Diffusion Models to solve the historical challenge of garment deformation in AI-generated imagery. By decoupled processing of texture, drape, and lighting, FashionAI allows brands to upload basic flat-lay or ghost-mannequin photos and instantly map them onto a diverse library of virtual human models across various ethnicities, body types, and poses. As of 2026, the architecture has evolved to support high-fidelity 8K output and semantic segmentation for granular control over fabric micro-details. Positioned as a direct competitor to traditional photography studios, Sharp's FashionAI drastically reduces time-to-market for seasonal catalogs and enables infinite A/B testing of model-product pairings. The infrastructure is built on a scalable cloud-native stack, offering enterprise-grade security and low-latency API endpoints for real-time virtual fitting room integrations.
Uses pixel-level attention masks to ensure fabric weaves (e.g., knitwear, lace) are not distorted during the model mapping process.
The semantic glue between product attributes and consumer search intent for enterprise retail.
The All-in-One AI Marketing Platform for E-commerce Growth and Content Automation.
Transforming legacy open-source e-commerce into autonomous AI-driven storefronts.
The lightweight, high-performance AI engine for rapid e-commerce deployment.
Verified feedback from the global deployment network.
Post queries, share implementation strategies, and help other users.
Generates consistent model poses across front, side, and back views for a single product.
Physically-based rendering (PBR) allows users to move light sources in a 3D-simulated space to match existing brand photography.
Parametric control over model BMI, skin tone (Fitzpatrick scale), and age demographics.
Deep learning vision models automatically detect and remove plastic mannequin parts and replace them with realistic human anatomy.
Automatically generates Alt-text and SEO tags based on the generated image content.
Allows Enterprise users to fine-tune 'Low-Rank Adaptation' weights to replicate specific house models.
Traditional photoshoots take weeks and cost thousands of dollars per collection.
Registry Updated:2/7/2026
Brands don't know which model demographic will drive the highest conversion for a specific item.
Marketing a western-centric photoshoot in Asian or Middle Eastern markets often sees lower engagement.