AI Platforms & Models

Model Orchestration

Once more than one model is in use, or once the cost of sending every request to a frontier model becomes visible on an invoice.

Orchestration routes each task to the model best suited to it, considering the nature of the work, cost, and latency. A single general model applies one cost and latency profile to everything, which means paying frontier prices for classification.

It is also the practical defence against lock-in: when routing sits above providers, capability can move between them as pricing and quality shift.

What the work includes

  • Routing rules based on task type rather than team preference
  • Cost and latency budgets enforced per route
  • Provider-agnostic interfaces so models can be added or replaced
  • Measurement of routing decisions against outcome quality
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// Common Questions

Questions
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Common questions about Model Orchestration.

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It routes each request to a model suited to it, rather than sending everything to one. Simple extraction can go to a small fast model while genuinely hard reasoning reaches a frontier one, so cost and latency track the difficulty of the task.

That depends entirely on your workload mix, and is measurable by classifying a sample of real requests before building anything. Any figure quoted without reference to your own traffic is describing someone else's workload.

Requests fail over to an alternative, which is one of the main arguments for routing across providers rather than committing to one. Failover has to be designed with the differences in mind, since models are not drop-in equivalents of each other.

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