New York-based apparel brand scaling retail operations and design with AI-driven merchandising
rag & bone operates a 201–500-person retail and design organization anchored in New York, with a tech stack spanning Adobe Creative Suite, Shopify, Dynamics 365, and modern data tools (dbt, Palantir Foundry, Power BI). Hiring is sales-heavy—64 of 92 open roles are in sales—while active projects center on inventory optimization, merchandising floor sets, and cross-channel collection launches. The adoption of AIOps signals operational scaling pressure as the brand manages multi-market retail logistics and sustainability compliance.
Notable leadership hires: Creative Director, Art Director, Design Director, Wholesale Director
rag & bone is a privately held apparel brand founded in 2002, headquartered in New York with operations across the US, France, and the UK. The company designs and distributes men's and women's clothing rooted in British tailoring, American workwear, and New York aesthetics. Core operations span visual merchandising, inventory management, pre-season assortment planning, and wholesale partnerships. Recent initiatives include sustainability programs in knitwear sourcing and an expansion of joint venture operations in Mexico. The organization is actively scaling sales and design teams while modernizing backend systems (Microsoft Dynamics 365, Azure, Power BI) to manage sell-thru, inventory accuracy, and retail store performance.
Design: Adobe Illustrator, Photoshop, InDesign, Capture One, 3D CAD. Retail/Operations: Shopify, Dynamics 365, ADP, Zendesk, SD-WAN. Analytics: Power BI, dbt, Palantir Foundry, Google Analytics, Looker. Also running Azure and Fabric on cloud infrastructure.
Headquarters in New York, NY. Active hiring in the United States, France, and United Kingdom.
rag & bone's technology stack, projects, and hiring signals are inferred from public hiring and company data — career pages, public listings, and company web presence — then clustered and de-duplicated. Figures are estimates that refresh over time. Read our full methodology →
This is not an official vendor or customer list. It is a technology-adoption signal inferred from public data, intended for B2B research.