Suave British Empire Shoots

Bernardo Camara & Danilo Borgato by Cesar Dutra for Rich FW 2012

The Rich FW 2012 look book is polished and suave. The series features slick apparel for both night occasions and casual outings. The editorial exhibits simple, yet sartorially intricate looks. The series features suiting separates, including slim, pleatless pants and a black satin tie. Also included is a pair of jeans and a graphic tee. The shoot was lensed by photographer Cesar Dutra.

Models Bernardo Camara & Danilo Borgato were put up against a giant Union Jack-embellished wall, allowing the clothing an extra gentlemanly vibe. The shoot was outfitted by stylist Thidy Alvis, who created the masculine, yet elegant looks. The Rich FW 2012 collection is both traditional and sleek, while still contemporary.

The Rich FW 2012 collection is perfect for the modern man with a laid-back style and swanky attitude.
Trend Themes
1. Night Occasions Apparel - Disruptive innovation opportunity: Develop a line of sustainable and eco-friendly night occasion apparel to cater to the growing demand for ethical fashion.
2. Sartorially Intricate Looks - Disruptive innovation opportunity: Utilize advanced 3D printing technology to create customizable and unique sartorial designs, allowing individuals to express their personal style.
3. Laid-back Style - Disruptive innovation opportunity: Create a subscription-based service that offers curated collections of laid-back style clothing, delivering convenience and personalization to customers.
Industry Implications
1. Fashion Apparel - Disruptive innovation opportunity: Integrate augmented reality into the fashion shopping experience, allowing customers to try on virtual outfits before making a purchase.
2. Photography - Disruptive innovation opportunity: Develop an AI-powered photography platform that automatically suggests creative compositions and angles to photographers, enhancing their artistic capabilities.
3. Styling Services - Disruptive innovation opportunity: Implement AI algorithms and machine learning to offer personalized styling recommendations based on individual preferences and body types.

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