Model Routing Strategy

Catch model routing failures on real traffic before users encounter them.

Teams are already dependent on single AI providers without realizing the full scope of the risk.

Match intent to model tier to cut token spend without sacrificing quality.

Real production performance looks nothing like academic benchmarks — measure what actually matters.

Users feel what matters most: how fast responses start and flow smoothly through completion.

Centralize fallback logic in a gateway to survive provider outages without duplicating retry code.

Teams waste more money defaulting to one expensive model than picking the right one for each task.

Governance and routing are the real production challenge for open-source coding models.