Member-only story
Route tickets and draft replies locally with Ollama or via API. #
During my time as an IT consultant at an SME, one of the most tedious problems I constantly faced was the morning support inbox. Someone always had to manually read and sort every single ticket, sifting through endless password resets and billing questions to find the few truly urgent issues. It was purely mechanical work.
In a previous article, I showed how to build a single data agent, the CSV Plot Agent. While perfect for beginners, single agents only get you so far. Real-world workflows need a team of specialized agents handing tasks off to each other, with the ability to route work back to a human when needed.
That’s why in this article, we are building a multi-agent triage system with LangGraph. One agent classifies the ticket, a router decides the next step, and another drafts a response. Any urgent cases are automatically escalated to a human. Best of all, we will design it to run seamlessly both locally with Ollama and via a cloud API using the exact same graph. (You can find the complete code in the GitHub repo linked below).
Let’s dive in.
Table of Content1 — From one agent to many: Why multi-agent systems? 2 — How LangGraph works: State, Nodes, and the Graph3 — Our Tech Stack: LangGraph, Ollama & an API Model 4 — Step-by-Step Guide Multi-AgentFinal Thoughts Where Can You Continue Learning?