How I Built an AI-Powered Customer Support Agent with n8n, OpenAI & Pinecone 🤖⚙️

Recently, I built a fully automated customer support agent using n8n — no more manual responses, just smart AI-driven support that runs 24/7.

🧠 Problem

Our team receives frequent questions about our FAQ, Policies, and Product/Service details. Manually responding to these is time-consuming and error-prone.

💡 Solution

I created an automation pipeline using n8n, which watches for relevant emails, classifies them, and responds intelligently using AI. Here's the stack:

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⚙️ The Stack

• n8n — Orchestrator & automation engine

• Gmail — Email trigger & response endpoints

• Google Drive — Source of truth (FAQ & Policy files)

• OpenAI Embeddings — To vectorize the knowledge base

• Pinecone — Vector search for semantic lookup

• OpenRouter Chat — AI conversation model to generate responses

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🔄 Workflow Breakdown

1. Gmail Trigger: Watches incoming emails

2. Text Classifier: Categorizes messages (Customer Support vs Other)

3. Google Drive Docs: Serves as the knowledge base for support content

4. OpenAI + Pinecone: Performs semantic search against stored vectors

5. AI Agent (via OpenRouter): Crafts a natural language response

6. Gmail Action: Labels the message and sends a reply

If the email is irrelevant, the workflow simply exits — no processing.

Here’s a visual of the flow in n8n:

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✅ Outcome

• ⏱️ Reduced response time to < 1 minute

• 📬 Automated replies for recurring queries

• 🧑‍💻 More focus time for our human team

• ⚡ Fully scalable — just add more data to Google Drive

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🔚 Final Thoughts

This project shows how powerful low-code tools like n8n can be when combined with LLMs and vector databases.

Would love to hear your thoughts or help others looking to build something similar!

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