AI Router vs AI Gateway: What's the Difference?
Short answer: not much. The terms describe the same category of infrastructure, and get used almost interchangeably — here's the distinction worth knowing anyway.
The short answer
Mostly, they mean the same thing: a layer that sits between your application and every AI model provider you use, making a decision about which provider handles each request. If you're searching for one term or the other, you're looking for the same category of infrastructure.
Why the terms overlap so much
"Gateway" is borrowed from API gateway terminology — a single entry point that fronts multiple backend services, which is a reasonably accurate description of what an AI gateway does for multiple model providers. "Router" describes the specific job that entry point does: deciding where each request goes. Most products that do one do the other, so the industry has largely stopped distinguishing them.
If you're being precise about it
A gateway is the broader architectural role — the single integration point, typically including things like authentication, rate limiting, and observability alongside routing. A router is more specifically the decision-making logic: given a request, which model handles it. In practice, a product marketed as an "AI gateway" almost always includes routing, and a product marketed as an "AI router" almost always includes the gateway functions around it — which is exactly why the distinction rarely changes what you'd actually evaluate.
Why it doesn't really matter which term you use
What matters is what the product actually does: does it give you one integration point for every provider, does routing account for the dimensions that matter to you (cost, quality, latency, and for Saudi enterprises specifically, data residency), and is it built with your market in mind. Mizan works as an AI gateway and an AI router — same product, whichever term you searched to find it.
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