European used and new car marketplace with AI-powered buying experience
Aramisauto operates a multi-country car sales platform across France, Spain, and Belgium, selling new and used vehicles through a digital storefront. The stack reveals a data-focused engineering org: Python, Pandas, scikit-learn, and XGBoost sit alongside LangChain and OpenAI, indicating active work on ML recommendation and conversational AI features. Hiring is sales-heavy (31 of 60 open roles) with junior staff concentration, typical of a scaling customer-acquisition phase, while the project backlog is dominated by digitalization of the purchase funnel and trade-in volume growth.
Aramisauto is a digital car retailer based in Arcueil, France, operating across France, Spain, and Belgium. Founded in 2001, the company acquired Spanish startup Clicars in 2017 and Belgian retail network Cardoen in 2018, consolidating regional car-buying operations under a unified European brand. The platform handles new and used vehicle sales across all makes and serves both direct purchase and trade-in workflows. With 501–1,000 employees, the business is operationally complex—managing inventory across multiple geographies, logistics, and procurement—while simultaneously investing in digital experience and ML-driven vehicle recommendation.
Python, Pandas, scikit-learn, XGBoost, LangChain, OpenAI, Snowflake, dbt, Vue, Nuxt, Elasticsearch, RabbitMQ, MongoDB, and Symfony. The mix of ML libraries and LLM frameworks indicates investment in predictive models and AI-assisted recommendation.
Primary focus areas include digitalizing the car purchase and trade-in processes, boosting trade-in volume, lead time reduction, and a virtual agent for vehicle recommendation. The project list also includes industrializing generative AI models and diagnostic optimization.
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