Decisions with context.
Try three predefined decision scenarios and inspect the constraints behind each selected route. No model inference or traffic routing is performed by this demonstration.
Route every
request with
context.
Explore how latency, cost, quality, capacity and availability can shape an inference decision.
The simulator cycles through three predefined scenarios. It does not call providers, score real models or route actual traffic.
{
"task": "customer_support",
"priority": "realtime",
"max_latency": 900,
"quality": "high"
}quality within 900ms SLA
Different tasks, different constraints.
| Scenario | Constraint | Illustrated selection |
|---|---|---|
| Customer support | A realtime task with a 900ms example latency budget and a high quality requirement. | Claude Sonnet · quality within the example budget |
| Autocomplete | A short interactive task where low predicted response latency is emphasized. | Groq / Llama · lowest predicted latency in the scenario |
| Batch summary | A less time-sensitive workload with a target quality requirement. | Gemini · lowest example cost at the target quality |
A decision is not a guarantee.
The simulator chooses from fixed examples. It does not predict provider capacity, establish a real SLA, measure model quality or evaluate your prompts.
A production routing policy needs validated constraints, fresh provider signals, failure behavior, cost definitions and an explicit account of how quality is assessed. Those service integrations are not implemented in this static preview.