multi-model-routing

What problem does it solve?

Multi-Model Routing prevents production agents from being brittle and overpriced by choosing the most suitable model provider per task and automatically falling back when providers degrade or fail.

Core Features & Use Cases

• Task classification to model selection: Dispatches tasks like code reasoning, structured extraction, long-context processing, and formatting to the model that best fits the workload.
• Cost- and latency-aware routing: Uses provider- and model-level cost/latency characteristics to meet budget and responsiveness targets.
• Per-provider circuit breakers with fallback chains: Avoids retry storms by detecting provider issues and switching to alternative providers in real time.
• Operational feedback loop: Feeds outcome and performance metrics back into the routing layer to refine model-task mapping over time.
• Unified execution interface: Normalizes how the agent calls models across Claude, GPT, and Gemini so the agent logic stays consistent.

Quick Start

Ask an agent to classify your workload and route each subtask to the cheapest model that meets your quality, latency, and availability constraints, using fallback providers if the primary one is unavailable.