Define the outcome. Not the provider.
A Lane describes how an AI workload should behave. ModelLane continuously finds a route that satisfies it — so your code asks for an outcome, and ModelLane picks the model.
A Lane is a production policy, not a model alias.
Instead of naming a provider in code, you name the outcome you need. Each Lane encodes quality, latency, cost, availability, retention, and region requirements. ModelLane evaluates available providers and routes every request to the one that satisfies the policy.
Production
Prioritize reliability and performance with automatic failover.
Economy
Minimum cost at an acceptable evaluation score.
Private
Zero-retention providers, approved regions, redacted logging.
response = client.responses.create(
model="lane:production",
input="..."
)
19 routing strategies. One Lane in your code.
Lanes are backed by the full routing engine. Define what matters and ModelLane executes the policy exactly — including failover, retries, and circuit breaking.