AI models differ a lot in price, speed and ability. Sending every request to the most powerful model wastes money on easy tasks, while sending everything to a cheap model hurts quality on hard ones. An AI router sits between your app and the models and makes that choice for each request automatically.
How Does an AI Router Work?
When a request arrives, the router first judges what kind of task it is and how hard it is. That judgment is often made by a small, fast model, sometimes a decision model. The router then picks a model and, for models that support it, a reasoning effort level, sends the request, and passes the response back. Many routers also fall back to another provider when a model is slow or unavailable, and they log which model answered each request.
Examples of AI Routers
OpenRouter, a service that gives one API for hundreds of models, offers routing options that pick a model for you. TypeSafe's Jev Router, listed on OpenRouter, runs on Jev and chooses the model and reasoning effort for each request. When we sent it a short prioritization question, it answered through a fast, low cost model rather than a frontier one, which is exactly the point: easy questions should not pay frontier prices.
AI Router vs AI Orchestration
A router answers one question: which model should handle this request. AI orchestration is broader. It coordinates a whole multi step workflow, deciding which steps run, in what order, and how results pass between them. A router is often one component inside an orchestrated system, handling the model choice at each step.
Why AI Routers Matter for Marketing Teams
Marketing teams run a mix of tasks through AI: tagging and classifying content, writing short ad variants, drafting long articles, analysing reports. Routing lets the cheap, quick tasks go to small models and saves the expensive models for work that needs them. For a team using AI every day, that can cut cost noticeably without a visible drop in quality.
What Are the Trade-offs?
- Less consistency: the same kind of request may be answered by different models, so tone and quality can vary.
- Harder debugging: when an answer is wrong, you first need to know which model produced it.
- Routing mistakes: a hard task sent to a small model gives a weak answer, so the router itself needs testing.
Frequently asked questions
What is an AI router?+
An AI router is a layer that picks which AI model handles each request, based on the task, quality needs, speed and cost, then forwards the request and returns the answer.
What is the difference between an AI router and AI orchestration?+
A router chooses one model for one request. Orchestration coordinates a full multi step workflow of models, tools and agents. A router is often one part of an orchestrated system.
Does an AI router save money?+
It can, because simple requests go to cheaper models and only demanding ones go to expensive models. The savings depend on your mix of tasks and on how well the router judges difficulty.