At CDAC, I developed a multilingual medical question-answering assistant using Python, LangChain, and large language models. I added FAISS-based vector search to retrieve medical context and built a Streamlit interface for users.
I also developed an autonomous text-to-SQL agent that turns natural-language questions into SQL queries. Its validation and error-correction workflows identify and revise unsuccessful queries.
For my customer churn and retention analysis project, I used Python and SQL to explore customer behavior and train classification models. I also created an interactive Power BI dashboard to examine churn across customer segments.
I completed a Post Graduate Diploma in Big Data Analytics at Centre for Development of Advanced Computing after earning a B.E. in Electronics and Telecommunication Engineering from MCT's Rajiv Gandhi Institute Of Technology. My project work includes data analytics, machine learning, and LLM-based applications.
