aaff is a 2,000-person professional services firm spanning accountancy, audit, tax advisory, and legal services across the Netherlands and South Africa. The tech stack is heavily Azure-centric (Data Lake, Synapse, OpenAI, Cognitive Services) with active adoption of data governance tools (Collibra, Informatica), signaling an internal push toward automation and data-driven compliance—a natural fit given their recurring pain points around process automation, financial administration, and tax compliance.
Notable leadership hires: Audit Director
aaff operates as a publicly owned professional services cooperative with over 50 office locations, primarily in the Netherlands. The firm serves mid-market and enterprise clients across accountancy, audit & assurance, tax advisory, corporate restructuring, and legal counsel. With ~2,000 employee-owners and no partner structure, the organization is scaling advisory capacity—evidenced by projects around new audit locations, cross-border advisory products, and international tax structuring. The hiring mix is heavily weighted toward finance (202 roles) and legal (50 roles), with emerging investments in data and automation capabilities.
aaff runs on a Microsoft Azure stack, including Data Lake Storage, Synapse Analytics, Databricks, and Azure OpenAI. They are actively adopting Collibra and Informatica for data governance and integration, supporting their automation and compliance initiatives.
Top priorities include automating accounting and payroll processes, optimizing financial administration, managing complex and international tax compliance, and reducing fraud risk—all drivers of their recent Azure and data governance investments.
aaff'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.