Explainable Model Routing for Agentic Workflows

1. 1Decompose complex tasks into specialized subtasks
2. 2Route subtasks to diverse models based on capability and cost trade-offs
3. 3Implement explainable model routing to provide transparency into routing decisions
4. 4Optimize workflows by balancing model capability and cost

AI engineers and researchers benefit from this approach as it provides transparency into model routing decisions, while developers can use it to optimize workflow efficiency

💡 Explainable model routing provides transparency into trade-offs between model capability and cost

🤖 Explainable model routing for agentic workflows: balancing capability & cost