GUIDES

An LLM router that returns a decision

Routing is a bounded choice: which of the models or paths you actually have should handle this task. Write the criteria down, let a decision model choose among your candidates, and keep the call itself in your code.

Label a held-out set, compare model decisions with it, and review errors before changing a workflow.
Label a held-out set, compare model decisions with it, and review errors before changing a workflow.

A router is a decision, not a proxy

A router does not hide the providers behind it, and it should not invent one. You supply the candidates you can really call, with their cost and latency, and the priorities that matter for this task. The answer is one of those candidate ids with a probability, not a paragraph about trade-offs.

Keep the criteria in writing for the same reason you keep classification labels in writing: two runs of the same question should not produce two different policies. If cost decides everything, say so; if quality decides and cost only breaks ties, say that instead.

Try the model-route tool · Request contract

Semantic routing is classification with another name

A semantic router maps an utterance onto one of a fixed set of routes, usually by comparing embeddings. That is the same job as a classifier with labels, so it inherits the same failure modes: a threshold that looks precise, an embedding model that drifts, and an out-of-scope message that still lands in the nearest bucket.

A typed decision over criteria you wrote keeps the route names and their boundaries explicit, and it returns the probability together with the choice. Neither approach is authorization: a route says which path fits, not that this user may take it.

What is Jev AI? · Text classification via API

Compare accepted results, not token prices

A cheaper model that fails a route costs more than the model you avoided, because the work is done again or a wrong answer reaches a customer. Evaluate each route separately on the same held-out examples, and count the errors where they are expensive instead of averaging them away.

Cost and latency per accepted result are the numbers worth tracking, next to the review rate your threshold produces. A published provider benchmark measures their tasks on their data; it is not a measurement of your traffic.

Evaluate before automating · Set confidence thresholds

Keep the fallback and the log

An unknown or low-confidence route belongs to a default path or to a person. Code that calls a model should treat a missing candidate as a failure to route, not as a licence to pick the largest model. Record the chosen candidate, the request id and the model version with the outcome, or the decision cannot be audited later.

Retry an uncertain connection with the same request id and unchanged input; a genuinely new task needs a new one. Routing a task to a model is not permission to run an irreversible action — that check stays where it already is.

Design human review · Plans and prepaid access

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Guides

What is Jev AI?

Jev is a structured decision model from TypeSafe, reached through OpenRouter. It evaluates context against questions and returns typed answers with probabilities, rather than composing a conversational response.

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