Campaign: Built as part of the Google Cloud Gen AI Academy APAC — "Meet the Builders" campaign.
Introduction
Hello community! My name is Ananya Raj, and I am a 2nd-year B.Tech Computer Science and Engineering student. Like most tech students, I love exploring new technologies and regularly use various free AI tools to make my coding, studying, and daily work easier.
However, as AI rapidly evolves from simple chat interfaces to autonomous, production-grade agents, I wanted to take a major step forward. I wanted to escape the "it works on my machine" loop, move my code out of isolated Jupyter notebooks, and build a real-world application that can be seen and reviewed by Google Cloud experts.
That is why I joined Cohort 3 of the Gen AI Academy APAC Edition! For my very first task, I am thrilled to introduce Marketera—an intelligent, safe, and conversational marketplace designed specifically for university campuses.
On any college campus, students are constantly buying, selling, or sharing resources—whether it's second-hand engineering graphics textbooks, lab coats, drafters, mattresses, or cycles.
Currently, this campus trading relies on disorganized WhatsApp groups, Telegram channels, or local forum threads. This creates massive friction:
Marketera is a smart campus marketplace assistant powered by Generative AI. Instead of wrestling with complicated filters, search terms, or endless chat messages, students can describe exactly what they need in plain, everyday language.
For example, a student can type: "I need a second-hand engineering graphics textbook and a drafter in good condition under ₹700, preferably near the library."
Marketera acts as an intelligent coordinator: it understands the request, extracts the constraints, searches active campus listings, ranks the matching items, and provides a friendly explanation of the recommendations.
Furthermore, to keep our campus environment clean and professional, Marketera integrates an automated Campus-Moderator layer to screen out spam, unauthorized off-campus listings, and inappropriate content before they ever go live.
Marketera handles student requests through a highly structured, agentic workflow:
To move Marketera from a local prototype to a robust cloud application, I leveraged Google Cloud's developer ecosystem:
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):Building Marketera taught me that the true power of AI lies in how we deploy it under real-world constraints. By transitioning from standalone prompting tools to architecting serverless cloud microservices on Google Cloud, I’ve learned how to design secure, scalable, and highly practical applications.
My next milestone is to finalize the deployment, secure feedback from the Gen AI Academy mentors, and pitch Marketera in the upcoming cohort Ideathon!
Are you a builder in Cohort 3? What local challenges are you tackling with Gemini? Let’s connect in the comments below!