Case Studies
Detailed breakdown of machine learning models, RAG systems, and engineering architectures.
ML SystemMachine Learning & Security
UPI Fraud Detection - ML System
Built a machine learning based system designed to detect fraudulent UPI transactions by utilizing data preprocessing, feature engineering, and model evaluation techniques.
Pythonscikit-learnPandasFeature EngineeringML Security
AI RAGAI Architecture & RAG
Explainable Customer Feedback Analysis
Graph-Based Orchestration & Emotion-Aware LLM Reasoning
Developed an explainable conversational RAG system for customer feedback analysis using graph-based orchestration, hybrid vector–knowledge graph retrieval, emotion-aware query handling, and evidence-grounded responses.
Neo4jQdrantGraph RAGLLM ReasoningVector Search