Dynamic AI model router for query optimization with OpenRouter
The Agent Decisioner is a dynamic, AI-powered routing system that automatically selects the most appropriate large language model (LLM) to respond to a user's query based on the query’s content and purpose. This workflow ensures dynamic, optimized AI responses by intelligently routing queries to the best-suited model. --- Advantages 🔁 Automatic Model Routing: Automatically selects the best model for the job, improving efficiency and relevance of responses. 🎯 Opti
At a glance
Dynamic AI model router for query optimization with OpenRouter is a ready-made n8n workflow you import as a workflow JSON file — no build required. It connects OpenAI, LinkedIn, Perplexity. It's free to download. Follow the 5-step import below to go live in minutes.
- Platform
- n8n
- Connects
- OpenAI, LinkedIn, Perplexity
- Modules
- 8
- Price
- Free
- Version
- v1.0

About this workflow
The Agent Decisioner is a dynamic, AI-powered routing system that automatically selects the most appropriate large language model (LLM) to respond to a user's query based on the query’s content and purpose. This workflow ensures dynamic, optimized AI responses by intelligently routing queries to the best-suited model. --- Advantages 🔁 Automatic Model Routing: Automatically selects the best model for the job, improving efficiency and relevance of responses. 🎯 Optimized Use of Resources: Avoids overuse of expensive models like GPT-4 by routing simpler queries to lightweight models. 📚 Model-Aware Reasoning: Uses detailed metadata about model capabilities (e.g., reasoning, coding, web search) for intelligent selection. 📥 Modular and Extendable: Easy to integrate with other tools or expand by adding more models or custom decision logic. 👨💻 Ideal for RAG and Multi-Agent Systems: Can serve as the brain behind more complex agent frameworks or Retrieval-Augmented Generation pipelines. --- How It Works 1. Chat Trigger: The workflow starts when a user sends a message, triggering the Routing Agent. 2. Model Selection: The AI Agent analyzes the query and selects the best-suited model from the available options (e.g., Claude 3.7 Sonnet for coding, Perplexity/Sonar for web searches, GPT-4o Mini for reasoning). 3. Structured Output: The agent returns a JSON response with the user’s prompt and the chosen model. 4. Execution: The selected model processes the query and generates a response, ensuring optimal performance for the task. Set Up Steps 1. Configure Nodes: - Chat Trigger: Set up the webhook to receive user messages. - Routing Agent (AI Agent): Define the system message with model strengths and JSON output rules. - OpenRouter Chat Model: Connect to OpenRouter for model access. - Structured Output Parser: Ensure it validates the JSON response format (prompt + model). - Execution Agent (AI Agent1): Configure it to forward the prompt to the selected model. 2. Connect Nodes: - Link the Chat Trigger to the Routing Agent. - Connect the OpenRouter Chat Model and Output Parser to the Routing Agent. - Route the parsed JSON to the Execution Agent, which uses the chosen model via OpenRouter Chat Model1. 3. Credentials: - Ensure OpenRouter API credentials are correctly set for both chat model nodes. 4. Test & Deploy: - Activate the workflow and test with sample queries to verify model selection logic. - Adjust the routing rules if needed for better accuracy. --- Need help customizing? Contact me for consulting and support or add me on Linkedin.
How to import this n8n workflow
- 1
Download the workflow JSON file after purchase.
- 2
Open n8n → click the menu → Import from File.
- 3
Select the downloaded JSON and import.
- 4
Set up credentials for each node that requires them.
- 5
Click Execute Workflow to test, then activate.
Setup guide
Setup guide included
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- JSON blueprint — instant download
- Setup guide PDF included
- 5 downloads · valid 30 days
- Works with n8n
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