Jev-router auto-picks the cheapest model per task

Most businesses using AI coding tools are still doing something simple, they pick one model and send every task to it. That’s easy to manage, but it can get expensive fast. A simple code change, a documentation update, and a complex debugging job do not all need the same level of model capability.

Jev-router is an open-source project built around a practical alternative. It routes each Claude Code task to the cheapest model it considers capable of handling the job. According to the project repository, it reached 126 GitHub stars at a rate of 65 per day, just two days after launch. That early attention suggests developers are actively looking for ways to control model costs without manually choosing a model for every request.

The important idea is bigger than coding. If your team is building AI agents for support, reporting, research, operations, or internal workflows, not every step needs your most expensive model. A sensible setup sends routine classification, extraction, and drafting work to lower-cost models, then reserves stronger models for decisions that need deeper reasoning or more reliable output. The challenge is setting the rules well, because routing something to a cheaper model only helps if quality stays acceptable.

This is the kind of thing we build into an AI command centre, where leaders can see which models are being used, what work they are handling, and where spend is rising.