Do You Actually Need an AI Gateway? (And When a Simple LLM Wrapper Isn’t Enough)

It always starts the same way. You add a single LLM call to your app. Maybe it’s OpenAI, maybe Anthropic. You test it, it works, and within a few hours you’ve shipped something that actually feels powerful. For a moment, it feels like the easiest integration you’ve ever done. And honestly, at that stage, it is. The problem is that this setup doesn’t stay simple for long. Another team hears about it and wants access. Then product asks if you can switch models for better results. Finance wants to know how much this is costing… and suddenly no one has a clear answer. Then security joins the conversation and asks the uncomfortable question: “Where exactly is our data going?” That’s usually when things stop feeling clean. API keys are scattered across services. Switching models requires code changes. Costs are vague. And when something breaks, there’s no single place to look. At this point, most engineers quietly start Googling: “Do I actually need an AI Gateway?” What an AI Gateway Actuall