Ketan Kauntia
Generalist Software Engineer

About
- Full Stack Developer based out of India.
- Currently Upskilling in System Design and DevOps.
- Previously explored RAG and Ai Agents
- I also have 7+ years of SEO & content writing experience.
Work Experience
X
Stealth Startup
March 2026 - Present
Graduate Engineer Trainee

StockInsights.ai
April 2024 - July 2024
SDE Intern

Technocollabs Software
January 2024 - March 2024
Full Stack Development Intern

Opensox.ai
October 2025 - December 2025
OpenSource Contributor
Education

Kalinga Institute of Industrial Technology, Odisha
2023 - 2025
Masters of Computer Applications - 8.90

Birla Institute of Technology Mesra, Jharkhand
2020 - 2023
Bachelor of Computer Applications - 8.33
Skills
Prisma
Docker
Proof of Work
Check out my latest work
I've worked on a variety of projects, from fullstack apps to AI agents
Patches Play : Online Puzzle Game
- A daily spatial-reasoning puzzle. Drag clean rectangles, satisfy every clue, fill the board. New levels, leaderboards, and shareable streaks coming soon.
- Helps kids & adults improve their congitive thinking instead of doom scrolling.
SEO
QuickSafe : Chrome Extension + Dashboard
- QuickSafe is the fastest way to save browser tabs, organise into categories, and access them from any device with a personal API endpoint.
- Built dashboard workflows for links, usage logs, and categories with real backend data wiring.
Prisma
Meeting Summarizer AI
- Spawns a Chrome instance using Selenium Webdriver to join and record the Google Meet sessions.
- Implemented real-time caption extraction from the DOM and Google Gemini API to generate meeting summaries.
WebSockets
Gemini API
GSoC Guide - Open-Source GSoC Tool
- Developed an interactive directory for exploring Google Summer of Code (GSoC) organizations with search, filters, and metadata aggregation
- Built to help students quickly find orgs by tags, languages, and past participation, improving discoverability and decision making
REST API
Vercel
MongoDb
Prisma
Financial RAG Pipeline
- Built a document ingestion pipeline to process financial PDFs across 30+ financial documents for a listed company.
- Implemented chunking using pdfplumber, generated vector embeddings for the chunks using OpenAI text-embedding-3-small, stored them in Supabase DB, and used Gemini API for summarization.
Gemini API
OpenAI Embeddings
PostgreSQL (pgvector)




