Routing Platform
A routing platform is an intermediary layer that automatically forwards each request to the appropriate AI model. Simple questions go to a cheap model, difficult ones to an expensive one — the user notices none of this.
Anyone building applications with artificial intelligence today has the choice between dozens of providers. Some programs that write texts or answer questions are fast and cheap. Others are slow and expensive, but noticeably more reliable at difficult tasks. A routing platform sits between the user and these programs and decides, for each individual request, who handles it. So you don’t send your question directly to a provider, but to the platform, and it makes the choice. The name comes from the English “to route” — similar to how a telephone switchboard distributes calls to the right department.
What operators save in costs with this
The most important reason for routing is money. Large language models charge per request, and the price differences between a small and a large model are often a factor of ten or more. At the same time, most requests in real applications are mundane: a greeting, a rephrasing, a short summary. Using the strongest available model for that is wasteful.
A second reason is independence from the provider. Anyone who ties their product firmly to a single model has a problem when its prices rise or the service goes down. Via a routing platform, a model can be swapped out without rewriting one’s own software. If a provider fails, requests automatically move to the next one.
Then there are legal requirements. A German company may only have certain customer data processed in data centers within Europe. A routing platform can specifically send such requests to European models and route everything else to the cheapest option worldwide.
How the platform selects the right model
The simplest variant is fixed rules that a developer enters by hand. For example: anything under 200 words goes to the small model, anything with program code goes to a specialized one. Such rules are easy to follow, but often miss the mark because short questions are not automatically easy questions.
More sophisticated platforms therefore place their own small model in front. It estimates how difficult each request is and routes it accordingly. This model is trained with sample requests for which it is known which target model still delivered a usable answer. It’s important that this pre-decision remains fast and cheap, otherwise it eats up the savings again.
A common misconception: routing does not make answers better, but at best equally good at lower cost. If the router chooses wrongly, the user gets a weaker answer than necessary. That’s why operators continuously measure how often a request had to be subsequently passed on to a stronger model.
Routing platforms in the market and in your own chat window
Well-known providers include OpenRouter, Not Diamond, or Martian, plus the routing functions of large cloud providers like Amazon or Microsoft. They offer a single interface for hundreds of models and bill centrally. For small companies, this is often cheaper than negotiating contracts with multiple providers individually.
Routing is now also built into products you use yourself. When a chatbot suddenly thinks longer and answers more elaborately on a difficult question, it has often internally switched to a stronger model. Providers don’t always call it that, but the principle is the same.
In business news, the term usually appears in connection with costs. When a company reports that it has halved its AI spending without reducing quality, a routing platform is often behind it. This is interesting for investors because it weakens the pricing power of individual model providers: whoever can switch at any time is less susceptible to being held hostage.
