Passion Edition

Submission: Edu-Insight Assistant

What I build

I built the Edu-Insight Assistant, a tool designed for educators to bridge the gap between complex school management data and actionable insights. It allows teachers to query students performance data using natural language, turning educational evaluation into a conversation rather than a manual data-processing task.

Demo

🔗 Link:

Passion-challenge

How I Built It

I utilized Next.js for a responsive, performant frontend and hooked it up to Google Gemini 3.5 API. The core logic involves a server-side API route that takes a teacher's natural language questions, prompt Gemini to generate the necessary SQL, and execute that query against a database. This architecture makes data exploration accessible to non-technical educators.

Prize Categories:

-Best Use of Google AI: Leveraged Gemini 3.5 Flash for natural language-to-SQL translation and result interpretation.

-Best Use of Snowflake:

Designed with an extensible data layer ready for production-scale analytical workloads in Snowflake.