I'm passionate about designing AI systems that combine creativity with technology. From Machine Learning and Deep Learning to LLMs, RAG, and AI Agents, I love building intelligent applications that make people's lives easier.
A LangGraph multi-agent chatbot for a music store — a supervisor agent verifies the customer and routes queries to specialized sub-agents with long-term memory.
Reads a customer email, drafts a structured, professional reply with an LLM, then simulates saving and sending it through API-like functions.
Scores a resume against a job description using a RAG pipeline — keyword matching plus FAISS retrieval, with anti-hallucination prompting for reliable feedback.
A conversational RAG app for chatting with your own PDFs — upload a document and ask questions grounded in its actual content.
A multi-agent system that generates, explains, and debugs code — a supervisor routes to specialized agents, with Stack Overflow-backed RAG for debugging.
A multi-agent pipeline that searches ArXiv, extracts and synthesizes papers, then outputs a PDF research brief and a Google Sheets summary.
Building RAG pipelines, structured-output extraction, and multi-agent workflows with LangChain and LangGraph across Groq, Gemini, and local model backends.
From classical models built from scratch to fine-tuned transformers, designing systems for classification, sentiment analysis, and cognitive scoring.
YOLO-based scoring pipelines, image preprocessing, and end-to-end deployment through Streamlit and Django for real-world use.