Building a Customer Support Agent with Gemini — Zero Training, Full Power

What if you could automate support emails using GenAI, embeddings, and a single notebook?

This is my Kaggle competition work V0

📝 Update: A more complete version of this project is available here:

👉 [Read the final project article] Here

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🧠 The Problem
Every support team deals with the same struggle: endless emails.
Refund requests, login issues, “Where’s my order?” — it adds up. Fast.

What if a GenAI agent could:

• Read incoming emails

• Understand the request

• Search past answers

• Write a helpful reply

All in one go. No training required.

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🛠️ The Solution (in 3 steps)
I built a working prototype of a support email agent powered entirely by Gemini.

Here’s how it works:

1. Zero-shot classification
   The agent reads the email and classifies it into one of 5 categories (refunds, account problems, etc.) using a natural language prompt — no training, just pure LLM reasoning.

2. Embeddings + Retrieval
   It then looks up the most relevant answer from a mini knowledge base of support content, using Gemini embeddings + cosine similarity. FAISS? Not even needed.

3. LLM-powered response
   Finally, it drafts a professional, friendly reply using the Gemini 2.0 Flash model, grounded in the retrieved support info.

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💡 What’s cool about this?

• No training. No fine-tuning. No extra infrastructure.

• Works out-of-the-box with Gemini + basic Python tools

• Clean, explainable, and fast enough to go live

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🧪 Tech Stack

• google-generativeai (Gemini Flash + embeddings)

• Pandas + NumPy

• Cosine similarity (no vector DB required)

• Gemini 2.0 Flash for generation

• All in a single notebook

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✅ GenAI Capabilities Demonstrated

• Document understanding

• Embeddings

• Retrieval-Augmented Generation (RAG)

• Grounding

• Zero-shot classification (optional few-shot if extended)

• Agents (multi-step logic)

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🚀 Try It Yourself
Here’s the full notebook (link to Kaggle or GitHub):
👉 See the notebook

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📈 What’s Next

• Connect to an invoice database

• Add feedback loop (human-in-the-loop editing?)

• Connect to Gmail

• Deploy as an API or frontend (Streamlit?)

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🧑‍🚀 Built for the Kaggle GenAI Capstone
This was my submission for the Kaggle x Google GenAI capstone project.
Shout out to the kaggle team — amazing course, and a great excuse to build something real.

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Let’s chat
Curious how to use GenAI in your product or team?
Hit me up on LinkedIn or reply here — I’d love to nerd out.