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Retail

Retail

Revolutionizing retail: Innovating shopping experiences for tomorrow

You are building a digital platform with specific demands: lots of integrations, demanding stability and performance, using cloud or being offered in a SaaS model, perhaps facilitating a two-sided market. You have a strong vision, a long roadmap and high ambitions. The technology you want to offer is complex and needs to be impeccable.

Exploring the intersection of digital and physical shopping experiences

The retail industry has many things happening today. By leveraging data, we can finally crack customer loyalty, offering online and in-store experiences that align with consumers’ desired products, as well as optimizing logistics, traceability, and predictability throughout the supply chain. Still a low margin industry, the demand for innovation is high. From food to fashion, what happens in retail impacts every consumer on a daily basis. 

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June 26th

The Cost of Choice

Most companies spend up to 40% to much on cloud, are you? Cut spend, not options. Smart standardizations win.

Cloud cost overruns and growing technical debt rarely stem from tooling alone—they are symptoms of architectural and operational choices. This session looks at how senior technical leaders can regain control by connecting cloud spend directly to business value. We’ll explore unit‑economics thinking, ownership models, and lifecycle management practices that reduce waste while preserving delivery speed. You’ll learn how to combine FinOps principles with technical‑debt controls to create a cloud environment that is financially sustainable and technically healthy.

May 28th

AI AGENTS DESERVE AI PLATFORM

Portable patterns for Azure, AWS and GCP that survive the next upgrade

AI agents are moving rapidly from experimentation into real production use cases, but architectures vary widely across cloud platforms. In this webinar, we compare practical patterns for building and running AI agents on Azure, AWS, and Google Cloud Platform. We’ll focus on what to standardize, where to embrace cloud‑native capabilities, and how to design for security, observability, and future change. The goal is not to pick a winner, but to help leaders understand how to scale agent‑based solutions without locking themselves into fragile designs.

April 23rd

Winning on Repeat: Product Engineering in the Age of AI

Cadence, quality and outcomes over output

Delivering a successful solution once is no longer enough. In the age of AI, organizations need product engineering models that enable them to win consistently across teams, releases, and markets. This session explores how leading organizations evolve from project‑centric delivery to product‑centric execution, supported by AI‑augmented engineering practices. We’ll look at cadence, quality, and accountability, and how leadership decisions shape sustainable delivery performance over time.

April 2nd

GOVERNING AI IN PRODUCTION

Designing cloud and data platforms that survive real-world pressure

Many organizations succeed in building AI proofs of concept, far fewer succeed in scaling them safely into production. This webinar focuses on what it takes to move from experimentation to reliable, governed AI platforms. We’ll discuss platform architecture choices, model governance, security, and policy patterns that enable teams to deploy AI at scale without slowing down delivery. Designed for senior technical leaders, this session provides practical guidance on turning AI initiatives into durable capabilities that deliver value beyond the first demo

March 5th

Navigating Digital Sovereignty and Strategic Cloud Choices

How Organizations Can Balance Innovation, Compliance, and Control in a Multi-Cloud World

In today’s rapidly evolving digital landscape, organisations face increasing pressure to ensure business continuity, maintain public trust, and comply with complex regulations like NIS2, DORA, and GDPR. This webinar explores the critical concepts of digital and operational sovereignty, the strategic importance of hybrid and sovereign cloud models, and the risks of vendor lock-in.