Coding tasks aren’t equally difficult, so why send every one to the same model? Smart Routing evaluates each task separately and selects the lowest-cost model capable of doing the job, helping balance model quality, latency and cost. In this demo, Omnigent splits an app build across planning, backend and frontend work, routes each task to a different model, and runs some of them in parallel.
Smart routing reliability only stabilizes when orchestration primitives are enforced across heterogeneous model layers. System efficiency depends on deterministic coupling of task signals with governed cost‑latency pipelines.
So valid , saving money and resources for every decision made helps us make the best of both AI usage and resource mangament
Choosing the right model per task is similar to assigning the right specialist to the right job. Better results and fewer wasted resources
Having the system decide when a simpler model is enough could make multi-agent development a lot more economical without forcing teams to compromise where deeper reasoning is actually needed.
Learn more: https://bit.ly/smart-routingai GitHub repo for this series: https://github.com/viktoriasemaan/agentic-ai-explained-labs s/o Viktoria Semaan