Omnichannel beauty marketplace with private D2C brands and 7M+ monthly users
Purplle operates a dual-channel beauty platform: a third-party marketplace (1000+ brands, 60,000+ products) paired with five owned D2C brands (FACES CANADA, Good Vibes, Carmesi, Purplle, NY Bae). The tech stack reveals a supply-chain and ML-forward operation—SAP + WMS for inventory, Kafka for event streaming, scikit-learn + TensorFlow + PyTorch for recommendation engines and content personalization. Hiring velocity is accelerating with 70 open roles, heavily skewed toward marketing and operations (24 combined), signaling aggressive expansion into offline retail and private-label manufacturing.
Notable leadership hires: Product Lead
Purplle is India's leading omnichannel beauty destination, founded in 2012 and operating across 6000+ offline touchpoints including 8 exclusive stores alongside its digital platform. The company powers 7 million+ monthly active users through personalized product recommendations, makeup-testing capabilities, and curated shopping experiences. Beyond marketplace operations, Purplle owns and scales five proprietary beauty brands. The organization spans 3000+ employees across product, engineering, operations, marketing, and design, with active projects ranging from new store buildouts and manufacturing scale-up to digital asset management and content production workflows.
Purplle uses Node.js, NestJS, and Express.js for backend services; MySQL and MongoDB for data storage; Kafka for streaming; Kubernetes for orchestration; GCP and AWS for cloud; SAP and WMS for supply-chain; and Python with scikit-learn, TensorFlow, and PyTorch for ML-driven recommendations.
Purplle is headquartered in Mumbai, Maharashtra, India, with a 3,000+ person team. The company operates 6000+ offline touchpoints and 8 exclusive stores alongside its digital marketplace.
Purplle.com'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.