- 🎓 B.Tech in Data Science & AI, GGSIPU (Delhi Technical Campus) — 2022–2026, CGPA 8.04
- 🔭 Building end-to-end GenAI & Agentic AI systems — RAG pipelines, multi-agent workflows, and LLM-powered applications, deployed and production-ready
- 🌱 Currently deepening my skills in LangGraph, MLOps, and scalable deployment pipelines
- 👯 Open to collaborating on ML/GenAI projects — RAG, multi-agent systems, time-series forecasting, and real-world business problems
- 🤝 Looking for guidance on MLOps and production-grade ML/LLM deployment practices
- 💬 Ask me about LangChain, LangGraph, RAG, Python, ML model deployment, and data-driven product solutions
- ⚡ Fun fact: I've shipped multiple GenAI apps live on Streamlit Cloud & Render — from AI video assistants to multi-agent research systems
🎥 AI Video Assistant Dual-engine transcription app (OpenAI Whisper + Sarvam AI for Hinglish) with RAG-based Q&A over video content, built using LangChain + Mistral AI + ChromaDB. Deployed on Streamlit Cloud.
🤖 Multi-Agent AI Research System A 4-agent pipeline (Search → Scraper → Writer → Critic) built with LangChain LCEL and Mistral AI, automating end-to-end research report generation.
📄 PDF RAG Assistant Document Q&A system using ChromaDB, Mistral AI embeddings, and MultiQueryRetriever for accurate, context-aware retrieval over PDFs.
🌆 City Intelligence System LangGraph-based agent integrating weather & news tools with human-in-the-loop approval for reliable, controllable decision-making.
📉 Customer Churn Prediction XGBoost-based churn model achieving 86% ROC-AUC, deployed on Streamlit Cloud with full feature engineering and evaluation pipeline.
🎬 Movie Recommendation System Content-based recommender using TF-IDF + cosine similarity, with a FastAPI backend and Streamlit frontend, deployed on Render.
😊 Emotion Detection (NLP Text-based emotion classifier using Logistic Regression + TF-IDF, achieving ~86% accuracy, deployed on Streamlit Cloud.
Languages & Core
GenAI / LLM / Agentic AI
ML / DL
Visualization
Deployment & Tools
