Building Support Agent Pro, an AI customer support agent that classifies tickets, retrieves grounded answers via RAG (FAISS + OpenAI embeddings), and escalates to a human when confidence is low. (Personal project — deep-diving into production LLM patterns like structured outputs, retries, and observability.)
👯 I'm looking to collaborate on
Open-source projects & full-stack applications built with Next.js, Spring Boot, and LLM-powered agent systems — especially anything involving Retrieval-Augmented Generation (RAG), structured LLM outputs, or human-in-the-loop AI workflows.
🤝 I'm looking for help with
Optimizing model efficiency for deployment and scaling RAG (Retrieval-Augmented Generation) pipelines for production-level apps.
🌱 I'm currently learning
The frontier of AI Orchestration: LangGraph, Multi-Agent Systems (MAS), and the Model Context Protocol (MCP) to build more autonomous developer workflows.
💬 Ask me about
- ☕ Java Backend: Spring Boot, Spring Security, and building robust User Management Systems.
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🌐 Full-stack Web: Creating real-time apps with Next.js, TypeScript, and Convex/Prisma.
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🧠 Problem Solving: Data structures and algorithmic logic (C++/Java).
⚡ Fun fact
I once built a five-step user-access resolution pipeline for an ERP portal that handled group grants, individual blocks, and deduplication all in one go! — at NITTTR Bhopal, M.P, India
Feel free to reach out — I love connecting with people!
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- 🚀 Profiles: Codeforces | LeetCode | GeeksforGeeks
- 💻 Core Language: Optimizing logic and writing efficient algorithms primarily using C++
- 🎯 Focus Areas: Advanced Data Structures, Binary Search on Answer, and Bit Manipulation
