Intent routing

Classify an incoming request into an intent and route each intent to the optimal handler: deterministic logic, a specialist model, or a human.

The pattern

1. Ask one choice question for the intent.
2. Map the chosen intent to a handler in code.
3. Fall back to a general handler when confidence is low.

---
accTitle: Intent routing
accDescr: A choice question classifies intent, and code dispatches to a deterministic handler, a specialist model or a human.
---
flowchart LR
  request["incoming request"]:::neutral
  intent["choice: intent"]:::accent
  router{"intent?"}:::warning
  deterministic["deterministic handler"]:::success
  specialist["specialist model"]:::primary
  human["human queue"]:::warning

  request --> intent --> router
  router -- "billing" --> deterministic
  router -- "technical" --> specialist
  router -- "other / low confidence" --> human

  classDef primary fill:#ede9fe,stroke:#7c3aed,color:#3b0764,stroke-width:1.5px
  classDef accent fill:#dbeafe,stroke:#2563eb,color:#0c4a6e,stroke-width:1.5px
  classDef success fill:#d1fae5,stroke:#059669,color:#064e3b,stroke-width:1.5px
  classDef warning fill:#fef3c7,stroke:#d97706,color:#78350f,stroke-width:1.5px
  classDef neutral fill:#f4f4f5,stroke:#a1a1aa,color:#18181b,stroke-width:1.5px

Example request

{
  "model": "typed-lm",
  "state": "I was charged twice for the same order and need one charge reversed.",
  "questions": {
    "intent": {
      "type": "choice",
      "instructions": "Which intent best describes the request?",
      "criteria": {
        "billing": "Double charges, invoices and refunds",
        "logistics": "Damaged, lost or late shipments",
        "account": "Login, profile and cancellation",
        "technical": "Product errors and setup"
      }
    }
  }
}

Combining in code

intent = response["answers"]["intent"]
if intent["confidence"] < 0.5:
    route_to_human(request)
else:
    handlers[intent["choice"]](request)

Why it works

Intent routing is a closed classification. A choice question with mutually exclusive, well-described options produces a reliable label; confidence tells you when the request is ambiguous.

Best practices

• Keep intents mutually exclusive and business-meaningful.
• Add an explicit other only if “other” is a real outcome.
• Use a hierarchy for large taxonomies: coarse intent first, then a second call.
• Re-check low-confidence requests instead of guessing.

Next steps

• Speculative fan-out — ask intent and other questions at once.
• Choice — the primitive.