.NET AI Performance Optimization: Reducing Latency and Costs

Last year, I inherited a .NET AI application that was struggling. Response times averaged 2.3 seconds, costs were spiraling, and users were complaining. After three months of optimization, we cut latency by 87% and reduced costs by 72%. Here’s what I learned about optimizing .NET AI applications for production. Figure 1: .NET AI Performance Optimization […]

Read more →

ML.NET for Custom AI Models: When to Use ML.NET vs Cloud APIs

Six months ago, I faced a critical decision: build a custom ML model with ML.NET or use cloud APIs. The project required real-time fraud detection with zero latency tolerance. Cloud APIs were too slow. ML.NET was the answer. But when should you use ML.NET vs cloud APIs? After building 15+ production ML systems, here’s what […]

Read more →

Building Production AI Applications with .NET 8 and C# 12

When .NET 8 and C# 12 were released, I was skeptical. After 15 years building enterprise applications, I’d seen framework updates come and go. But this release changed everything for AI development. Let me show you how to build production AI applications with .NET 8 and C# 12—using actual C# code, not Python wrappers. Figure […]

Read more →

Introducing Monocross – A cross-platform MVC pattern for mobile development in .NET/C# and Mono

I am evaluating different cross platform mobile development solutions. This is just a quick introduction to a framework I came across. What is cross platform mobile applications? A mobile application developed in such a way that it will work or run on most of the mobile platforms such as Android, iOS, Windows Phone, Blackberry etc. […]

Read more →