From AI Prototype to Production: The Technical Architecture Enterprises Need
Building a generative model that spits out flawless answers in a controlled notebook feels like a massive win for any engineering team. But watching that exact same model crash the second it hits real, concurrent user traffic? That is a frustrating reality check. The gap between a slick proof of concept and a mission-critical deployment is surprisingly wide, and it almost always comes down to the underlying infrastructure. If your systems cannot handle the dynamic load, the smartest algorithm in the world will not save you.