Token spend isn’t going down. You need more than naive routing to manage it

The rising cost of token usage for AI agents presents a significant challenge for scaling AI applications. Manually tuning agents and creating routing rules is slow and becomes obsolete as models evolve, leading to inefficiencies. A common strategy to manage this is routing, where tasks are sent to the most cost-effective model that can handle the job. To address this, an intelligent router is being developed to automate waste reduction and optimize routing decisions at runtime. This automated approach aims to cut costs significantly without sacrificing agent quality, making large-scale AI deployment more financially viable.