Agricultural trading and supply company across crops, livestock feed, and farm technology
AGRAVIS Raiffeisen AG is a large German agribusiness wholesaler and retailer operating across crop inputs, animal nutrition, farm equipment, energy, and building materials. The tech stack is dominated by SAP (ERP, S/4HANA, MM, SD, FI, SuccessFactors, Transportation Management) with modern BI and data layers (Power BI, Azure, SAP Datasphere, Stibo STEP), indicating an enterprise in the middle of a major systems consolidation—active projects include full SAP transformation and data governance overhaul—paired with lean product engineering (1 engineer in active hiring) and mid-level sales/finance hiring, suggesting operational execution and supply-chain optimization are the near-term focus.
AGRAVIS Raiffeisen AG operates as an integrated agricultural trading company headquartered in Münster, Germany, serving farmers and rural businesses across four primary segments: agricultural products (crop inputs), animal nutrition (livestock feed), farm technology, and energy/building materials retail. The business is structured around complex supply-chain logistics—order-to-delivery workflows, inventory management, seasonal demand patterns, price volatility in commodity markets, and timely material availability (especially fertilizer supply) are documented pain points. The organization employs 5,001–10,000 people and is actively scaling sales, finance, HR, and data functions.
SAP (ERP, S/4HANA, FI, SD, MM, Transportation Management, SuccessFactors), Microsoft Fabric, Azure, Power BI, SAP Datasphere, Stibo STEP, and custom ABAP/JavaScript code. Stack is enterprise-grade with heavy investment in data governance and master-data management tooling.
SAP transformation (including S/4HANA migration), data governance for master-data, risk management system development, Stibo STEP implementation, and optimization of order-to-delivery processes across fertilizer, feed, and equipment supply chains.
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AGRAVIS Raiffeisen AG'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.