European refurbished electronics marketplace with AI-driven revenue optimization
refurbed operates a multi-category refurbished goods marketplace across Europe with a tech stack anchored in Vue + TypeScript frontend and Go + gRPC backend, backed by PostgreSQL, Redis, and GCP infrastructure. The organization is heavy on data science (PyTorch, TensorFlow, scikit-learn, BigQuery, pandas) relative to its size, with active projects in AI-driven analytics and e-commerce revenue optimization—indicating a shift from logistics-first to predictive pricing and demand modeling. Leadership gaps in data and engineering (only 1 staff-level hire) paired with accelerating hiring velocity suggest scaling infrastructure strain.
refurbed operates a European online marketplace for refurbished electronics, spanning consumer electronics, sports, and expanding categories. The company processes products through a 40-step refurbishment workflow and positions them as cheaper and more sustainable alternatives to new goods. With roughly 300 employees distributed across Austria, Germany, Switzerland, and hiring into Bulgaria, Indonesia, and Sweden, refurbed operates a seller-buyer dual marketplace model. Current operational challenges center on delivery and returns inefficiencies, seller acquisition, and scaling into new geographies and product categories.
Frontend: Vue, TypeScript, JavaScript, Tailwind CSS. Backend: Go, gRPC, PostgreSQL, Redis, RabbitMQ. Infrastructure: Kubernetes, GCP, BigQuery. Data/ML: Python, pandas, scikit-learn, PyTorch, TensorFlow, OpenCV. Analytics: Looker, Tableau.
Austria, Bulgaria, Germany, Indonesia, and Sweden. HQ is Wien (Vienna).
Other companies in the same industry, closest in size