Building a Customer Support Agent with Gemini β 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
π Update: A more complete version of this project is available here:
π [Read the final project article] Here
π§ The Problem
Every support team deals with the same struggle: endless emails.
Refund requests, login issues, βWhereβs my order?β β 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.
π οΈ The Solution (in 3 steps)
I built a working prototype of a support email agent powered entirely by Gemini.
Hereβs how it works:
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 β no training, just pure LLM reasoning.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.LLM-powered response
Finally, it drafts a professional, friendly reply using the Gemini 2.0 Flash model, grounded in the retrieved support info.
π‘ Whatβs 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
π§ͺ 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
β GenAI Capabilities Demonstrated
Document understanding
Embeddings
Retrieval-Augmented Generation (RAG)
Grounding
Zero-shot classification (optional few-shot if extended)
Agents (multi-step logic)
π Try It Yourself
Hereβs the full notebook (link to Kaggle or GitHub):
π See the notebook
π Whatβs Next
Connect to an invoice database
Add feedback loop (human-in-the-loop editing?)
Connect to Gmail
Deploy as an API or frontend (Streamlit?)
π§βπ Built for the Kaggle GenAI Capstone
This was my submission for the Kaggle x Google GenAI capstone project.
Shout out to the kaggle team β amazing course, and a great excuse to build something real.
Letβs chat
Curious how to use GenAI in your product or team?
Hit me up on LinkedIn or reply here β Iβd love to nerd out.