From Experimentation to Industrialized, Compliant AI By Praveen Kumar Adepu, Technical Lead AI & Data Analytics, beON consult GmbH The biggest barrier to successful AI is not model complexity—it is the ability to operationalize AI at scale in a secure, governed, and compliant manner. In many organizations—particularly in regulated industries—AI initiatives remain stuck at
By Sridhar Narini, Chief Innovation Officer, beON consult GmbH Most organizations don’t suffer from a lack of data—they struggle because their data platforms were never built for today’s demands: real-time processing, massive scale, and AI-driven innovation. The Lakehouse is not just an architectural evolution; it represents a fundamental shift toward treating data as a
Artificial Intelligence is no longer optional – it’s the engine of competitiveness. Yet many organizations still struggle to turn AI into measurable business value. Why? Because AI only works when data quality, a clean core, and seamless integration come together. Our core belief: The long-term success of AI begins with a strong Data Foundation and
As mainstream support for SAP Business Warehouse (BW) 7.5 approaches its end (2027, with extended support until 2030), organizations are under increasing pressure to make strategic decisions about the future of their data platforms. Simultaneously, the growing need for agility, real-time data access, cloud readiness, and self-service analytics is driving a shift toward modern, scalable
As a trusted IT consultancy for highly regulated sectors, beON enables organizations to engineer resilience and compliance into their core technology platforms. Our DevSecOps frameworks are not just automation pipelines — they’re policy-driven, audit-ready, and security-first by design. Below, we illustrate how we integrate security, observability, and compliance at every layer of modern application and infrastructure delivery. ICT
From Chatbots to Hyperautomation: AI Services That Future-Proof Insurance, Banking, Industry, and Defense How beON Brings AI Innovations to Highly Regulated Industries In large enterprises with vast data volumes and strict regulatory frameworks – such as banks, insurance companies, or defense organizations – the use of cloud-based AI applications adds extra complexity. Along with country-specific
