https://murateksi.com/tags/ai/Recent content in AI on Murat EksiHugoen-usTue, 10 Mar 2026 00:00:00 +0000https://murateksi.com/case-studies/industrial-predictive-maintenance/Tue, 10 Mar 2026 00:00:00 +0000https://murateksi.com/case-studies/industrial-predictive-maintenance/The customer had a simple idea: if their platform could tell operators which machines were likely to fail before they failed, the customers would pay a premium for that signal. The idea was right. The path to production was not the one anyone planned. The problem with the obvious approach Predictive maintenance models learn from failure events. To predict a bearing failure, you need historical data showing what the sensor readings looked like in the hours and days before the bearing actually failed.https://murateksi.com/posts/building-ai-ready-architecture/Thu, 05 Mar 2026 09:00:00 +0100https://murateksi.com/posts/building-ai-ready-architecture/The most common question I hear from engineering leaders right now is some version of “how do we add AI to our platform?” It is a reasonable question. It is also usually the wrong first question. The right first question is: can your current architecture support AI workloads reliably? Not just technically, but operationally. In practice, most enterprise architectures were not designed with the access patterns, latency profiles, or cost structures that AI workloads require.https://murateksi.com/posts/enterprise-ai-adoption-reality/Thu, 18 Dec 2025 09:00:00 +0100https://murateksi.com/posts/enterprise-ai-adoption-reality/I have watched dozens of enterprise AI initiatives launch with real executive buy-in and stall within six months. The pattern is consistent enough that I can usually predict which ones will make it by the end of the first architecture review, before a line of model code has been written. The model works on clean data. Production data is not clean. The question nobody wants to ask first Every AI conversation in an enterprise starts with “what model should we use?