AI Gateway Part 2: MuleSoft LLM Proxy | Model Based Routing Explained | Static Routing

Learn how to implement model-based routing using MuleSoft LLM Proxy in a complete end-to-end demo. This video shows how to dynamically route requests to different LLM providers based on logic, cost, or use case.

As AI adoption grows, choosing the right model for each request is critical. In this tutorial, you’ll build a MuleSoft-powered LLM proxy that intelligently routes traffic across models while maintaining governance, flexibility, and performance.

🔑 *Key Highlights:*
• Build an LLM Proxy using MuleSoft
• Implement model-based routing logic (OpenAI, others)
• Dynamically select LLMs based on request Model
• Apply policies for control, security, and observability
• End-to-end demo with real routing scenarios
• Best practices for multi-model AI architecture

Видео AI Gateway Part 2: MuleSoft LLM Proxy | Model Based Routing Explained | Static Routing канала Mule Ace Academy