Building tools that make AI actually useful.
Final-year CS student at SJCE, Mysuru. I ship things — developer tools, AI pipelines, feedback systems. Interested in roles where I can own hard problems from day one.
AI-powered product intelligence platform. Bridges customer feedback and engineering decisions — think Cursor, but for product managers. Decision Records let teams attach customer evidence to every build choice. Integrates with GitHub and Linear.
Next.js TypeScript Supabase Groq (Llama) Vercel
CLI framework for LLM prompt regression testing. Plugs into CI pipelines and compares baseline vs. candidate prompts across accuracy, hallucination rate, latency, and cost. Model-agnostic, MIT licensed.
Python CLI LLM APIs CI/CD
Go CLI tool for AI-assisted development workflows. Optimized the agent loop for high-throughput performance and reduced system prompt token usage by ~60%.
Go LLM APIs CLI
Cross-platform sleep coaching app. Pulls data from Google Fit, runs habit analysis with TensorFlow, and surfaces personalized recommendations via GPT-4.
Flutter TensorFlow GPT-4 Google Fit
Multithreaded Huffman compression engine in C++. Uses producer-consumer concurrency for high-throughput file compression and decompression.
C++ Multithreading Systems
Languages — Python, TypeScript, Go, C++, Dart
Frontend — React, Next.js, Tailwind CSS, Flutter
Backend — FastAPI, Node.js, Supabase, Firebase, MongoDB
AI/ML — OpenAI, Anthropic, Groq, TensorFlow, LangChain
Infra — Docker, GitHub Actions, Vercel
Open to early-stage startup roles (full-time or internship) in AI, backend, or full-stack engineering.