"Model routing" is spreading as a builder pattern independent of Ramp's own PR.

Two unrelated projects surfaced this week with the same idea: route simple tasks to cheap models, hard tasks to expensive ones, and watch your bill drop. One is Ramp Router, which got a shoutout from a prominent AI engineer. The other is an open-source agent CLI called KlaatAI that claims 10x cost cuts through smart routing. Neither team coordinated. They just arrived at the same answer.

The pattern is straightforward. Most AI workflows include steps that do not need GPT-4 or Claude Opus. Summarizing a bullet list, checking a date format, extracting a name from structured text. Those can run on a model that costs a fraction per token. Routing logic sits in front, decides which model handles which step, and sends the request accordingly. The savings compound fast if you run hundreds or thousands of calls a day.

This is not a feature locked inside one vendor’s platform. It is a builder pattern, and it is spreading because the economics are obvious. If you are running agents that chain multiple LLM calls together, you are almost certainly overpaying unless you have routing in place. The fact that two separate projects landed on this in the same week tells you it is becoming table stakes, not a novelty.

We are building routing logic like this into the Omni Command Centre because cost control matters as much as capability when you scale AI across a business. You do not need to rewrite your workflows. You need a layer that makes the right model choice for each step without you thinking about it. If your AI spend is climbing and you have not looked at routing yet, now is the time.