About Vaishnavi Bharambe
I'm a B.Tech Information Technology student at Walchand College of Engineering, Sangli, and a Siemens Scholar (Batch 11). I like questions that a dataset can answer: who your most valuable customers are, which ones are about to become valuable, and what to do about each group.
This summer I interned with the cybersecurity team at Siemens, where I built reports and automated workflows with Excel, Power BI, SharePoint and Power Automate. Outside class I build end-to-end projects in Python, and I am now moving into AI with retrieval-augmented generation (RAG) and transformer models.
Projects
High-Value Customer Identification: Fintech customer segmentation
A weighted Customer Value Score and K-Means segmentation that finds the most valuable bank customers today, and the ones most likely to grow.
Tech: Python, Pandas, NumPy, scikit-learn, Matplotlib, Seaborn, Excel
Source code
DocuMind: RAG document assistant
Upload PDFs and ask questions in plain English. Answers come only from your documents, with the file and page cited for every fact.
Tech: Python, Streamlit, ChromaDB, Sentence Transformers, Groq, Ollama, pypdf
Source code
Legal Case Outcome Prediction: NLP for Indian law
Upload an Indian court judgment and a fine-tuned InLegalBERT model predicts its jurisdiction and appellate outcome, with SHAP showing which phrases drove the decision.
Tech: Python, InLegalBERT, Hugging Face, SHAP, PyMuPDF, Streamlit, Supabase
Source code
SafeLinker: Phishing URL detection
A real-time phishing URL detector that combines rule-based checks with a soft-voting ensemble of XGBoost and Random Forest, and explains why a link was flagged.
Tech: Python, scikit-learn, XGBoost, Pandas, NumPy, Streamlit, Plotly
Source code · Live demo