There is a constant discussion about the potential of AI, but far too little about the actual architecture behind a successful implementation. In this week’s episode, I sit down with Konrad Jelen, who works with Kolomolo and StackRails, to break down exactly what it takes to integrate AI into large, complex organizations.
With decades of operational experience in data science and business automation, Konrad shares concrete frameworks for moving from isolated experiments to measurable business impact. We review real-world cases from Swedish enterprise companies in telecom and finance, where the right system architecture has reduced manual work by over 90 percent and identified anomalies with 98 percent accuracy. The focus is entirely on building systems that genuinely optimize the business and automate processes at scale.
A major part of the conversation revolves around security, governance, and control. Rolling out AI in production requires a robust infrastructure. Konrad shares insights into how organizations can develop, monitor, and govern AI solutions at scale with full compliance, as well as the technical requirements for making it happen.
This is an episode for those of you who drive AI initiatives or lead data science teams and want to stop guessing. It provides a concrete blueprint of how leading companies actually build and scale their systems in production.
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