Commercial refrigeration systems and turnkey solutions for retail and food service
Epta is a multi-brand refrigeration manufacturer operating across 40+ branches and 10+ production facilities worldwide, with significant SAP infrastructure (S/4HANA, BW, Analytics Cloud, Datasphere) paired with emerging ML tooling (Python, scikit-learn, TensorFlow, PyTorch). The engineering-heavy hiring velocity—21 open roles in engineering alone, accelerating across 10 countries—combined with active projects in equipment design and system optimization suggests a push toward custom, digitally-connected solutions. Pain-point data reveals operational maturity challenges: data accessibility/quality gaps and analytics delivery latency indicate incomplete ERP-to-insight translation despite advanced SAP deployment.
Epta manufactures commercial refrigeration systems under six heritage brands (Costan, Bonnet Névé, Eurocryor, Iarp, Kysor Warren, Hauser), serving Retail, Food & Beverage, and Ho.Re.Ca. customers across 100+ countries. The company operates as a vertically integrated system provider: product lines span positive and negative display cases, plug-in units, and large-scale power packs, supported by three service divisions (EptaConcept, EptaTechnica, EptaService) that bundle custom design, installation, and maintenance. With 5,001–10,000 employees based in Milan, Epta positions itself on energy efficiency, digital connectivity, and sustainability compliance—core themes in its current project portfolio around turnkey deployments, cooling system reliability, and workplace safety.
Epta runs a deep SAP ecosystem (S/4HANA, BW, Analytics Cloud, Datasphere, WM, MM, EWM) for enterprise operations, complemented by Salesforce for CRM, AutoCAD for design, and emerging ML libraries (Python, scikit-learn, TensorFlow, PyTorch) for analytics.
Milan, Lombardy, Italy. The company operates 40+ technical and commercial branches and 10+ production facilities globally, employing 5,001–10,000 people.
EPTA GROUP'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.