At Exavalu, I design and deploy end-to-end ML pipelines for enterprise insurance datasets, processing more than 100K rows with Python, Pandas, and NumPy. I also developed ML-based schema mapping across systems, engineering 16 mapping features.
I build LLM-agent data-quality solutions with rule-based validation and remediation. I presented solutions to enterprise clients, contributed to a key deal, and received a Certificate of Appreciation.
During my AI/ML internship at Kalyani Government Engineering College (KGEC), I designed an 8-agent clinical AI architecture for heterogeneous clinical reports. I also designed clinical NLP and RAG workflows grounded in medical terminology resources and clinical guidelines.
My projects include DQ_Validator, a multi-agent platform for assessing and remediating data quality, and a source-to-target mapping tool that ranks candidate schema mappings. I also built and Dockerized a FastAPI RAG assistant for source-grounded document Q&A.
