Nishant Nirmal

Built a full-stack AI-enabled library platform with role-based dashboards and modules for catalog management, borrowing workflows, payments, and analytics. Integrated semantic book discovery using Gemini embeddings and vector similarity search, enabling natural language queries across library datasets. Architected a Retrieval-Augmented Generation (RAG) pipeline to power AI book recommendations and contextual search responses. Created AI reading roadmap generation and personalized recommendations using user behavior embeddings.

Built an AI-powered customer support assistant for the game "Raji: An Ancient Epic". Applied Retrieval-Augmented Generation using FAISS vector search and sentence-transformer embeddings for semantic knowledge retrieval. Constructed an automated ticketing system that classifies issues by category and priority while extracting device information. Engineered an AI Copilot module that detects similar historical issues using embedding similarity and generates solution suggestions.

Built a multilingual language classification system using an RNN model trained on labeled text data. Developed text preprocessing, tokenization, padding, and a confidence-based prediction pipeline. Deployed the model using Streamlit for real-time inference and visualization.