Multi-Agent AI in n8n: 3 Parallel Agents for Competitive Intelligence

Agentic AI is the hottest topic in software development right now. Every week there is a new framework — LangChain, CrewAI, AutoGen, LlamaIndex Workflows — promising to make multi-agent systems accessible. But if you are already using n8n for automation, you can build a surprisingly capable multi-agent pipeline today with no new dependencies, no Python environments, and no infrastructure changes. This article walks through a competitive intelligence pipeline that spins up three specialized AI agents, runs two of them in parallel, then synthesizes their outputs into a structured research report. The whole thing triggers from a webhook and logs results to Google Sheets. Section 1: The Architecture Here is the full workflow at a glance: Webhook Trigger └── Validate Request (Code node) ├── Agent 1: Market Analyst ──────────┐ │ ├── Merge Node (waitForAll) └── Agent 2: Competitor Analyst ───────┘ └── Code Node: Merge Results └── Agent 3: Strategy Synthesizer └── Respond to Webhook └── Google