AI Engineer
RAG systems
Fine-tuning LLMs
Agentic Engineering
Engineered AI-powered legal intelligence transforming the legal ecosystem for lawyers, law firms, corporates, and judiciary.
Simplified legal research, drafting, and documentation while delivering intelligent insights for complex legal scenarios.
Developed cutting-edge AI agent architectures enabling real-time collaboration between autonomous systems.
Building an AI copilot that assists developers in writing cleaner, faster, and more efficient code.
Applied AI-driven feature engineering and statistical modeling to optimize predictive healthcare diagnostics with focus on green skills.
Completed training in Cybersecurity Essentials and Network Security Fundamentals.
Gained hands-on experience in securing networks and identifying vulnerabilities.
Fine-tuned on Gemma 4 E4B via QDoRA using the Unsloth framework. Runs fully offline on a ₹8,000 Android phone, measures vital signs from the camera and reasons over real clinical trajectories.
Telegram-native ReAct agent loop with 20 integrated tools, LLM routing, Qdrant vector memory, Supabase persistence, and DuckDuckGo live web search.
Agentic RAG chatbot using Model Context Protocol with multiple agents for document ingestion, ChromaDB vector storage, and Google Gemini API for multi-format Q&A via Streamlit.
Naive Bayes classifier served as a FastAPI REST microservice on Hugging Face Spaces. Automated support-ticket processing with TF-IDF vectorization and regex preprocessing.
Transforms an old laptop into a dual-boot AI server running Ubuntu Server and Windows. The server is fully wireless, allowing for AI interaction using Ollama and implementing Database + Retrieval-Augmented Generation (RAG) for enhanced AI responses.