A simple routing example
A company may send language detection and short classification to a fast small model, while routing a contract summary or difficult research question to a larger model. The router can use rules, a classifier, a confidence score, or a second model to choose.
What the router needs
- A task taxonomy or routing signal.
- Measured quality thresholds for each route.
- Fallback behavior when a model is unavailable.
- Cost and latency limits.
- Logging that records the route and outcome.
The hidden risk
Routing can make a system harder to reason about. If quality falls, you need to know whether the input was classified incorrectly, the chosen model failed, or the fallback changed the result. Start with explicit rules and compare them against a fixed evaluation set before adding a learned router.