- ๐ญ Pronouns: He/Him.
- ๐ฑ Backend & AI/ML dev who enjoys messy problems and clean solutions
- ๐ Building AI-powered systems, breaking them, then fixing them better
- โ๏ธ Strong believer in clean abstractions and measurable impact
- โก Build. Break. Fix. Improve.
- Backend & Systems : Java, Spring Boot, Node.js, Express, Python, REST, gRPC, PostgreSQL, MySQL, Redis
- Frontend : React, Next.js, TypeScript, Tailwind CSS
- Cloud & DevOps : AWS, Docker, Kubernetes, CI/CD (GitHub Actions, Jenkins), Linux
- Data, AI & Observability : SQL, Elasticsearch, machine learning pipelines, Generative AI (LangChain, RAG, LLMs)
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LLM Router MCP โ MCP server that intelligently routes prompts across Gemini and Groq/Llama based on task intent (planning, codegen, testing, review), minimising token cost without sacrificing quality. Published as an npm package; integrates natively with Claude Desktop, Cursor, and VS Code.
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Splitr โ Full-stack expense splitting app built with React, TypeScript, and Supabase. Features a minimum-payment settlement algorithm, guest mode with automatic cloud migration on sign-up, UPI deep-link payments, and Row Level Security enforced at the database level. Deployed at splitr-lyart.vercel.app.
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Handwritten Equation Solver โ Deep learning pipeline combining a CNN (96.97% character accuracy) with an RNN for sequence interpretation to recognise and solve handwritten mathematical equations from images. Served via a Streamlit web app with a live drawing canvas.
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Ledger โ Personal finance dashboard built with React and FastAPI, backed by MongoDB. Tracks bills, recurring subscriptions with billing cycle normalisation, and tasks with priority levels โ with an AI insights layer that flags unused subscriptions and upcoming payment risks.
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YouTube RAG Chatbot โ AI-powered chatbot that transforms any YouTube video into an interactive Q&A experience using LangChain and Retrieval-Augmented Generation, achieving 25โ35% improvement in answer relevance over baseline LLM responses.
- Contributing to open source and community-driven projects.
- Building and learning backend development with Java, Spring Boot, and RESTful APIs.
- Exploring cloud, distributed systems, and applied machine learning.
- Open to internships and entry-level roles focused on real-world problem solving.



