A comprehensive GenAI application that demonstrates multiple AI capabilities including document summarization, code explanation, portfolio generation, and intelligent Q&A systems.

Developed an AI-powered tool that summarizes PDFs and articles and answers user queries using Large Language Models (LLMs). Integrated a Node.js backend with APIs for real-time responses and planned RAG implementation to enhance contextual accuracy and retrieval performance.

DocInsight: Intelligent PDF Summarizer + Q&A System with RAG

Multimodal Knowledge Assistant — an AI-powered system for summarization and intelligent Q&A over unstructured data.

AI-powered news analysis system leveraging RAG (LangChain, LangGraph, ChromaDB) for semantic retrieval, summarization, and intelligent Q&A.

A powerful AI-powered knowledge management and research platform. featuring document management, intelligent summarization, Q&A capabilities, RAG system, and MCP (Model Context Protocol) integration.

This project integrates two core natural language processing functionalities: a Q&A chatbot and a text summarization system. The Q&A chatbot allows users to ask questions and receive intelligent, context-aware responses, while the text summarization module converts long passages of text into concise and meaningful summaries.

AI Document Summarizer & Q&A System (PDF, DOCX, TXT) — Powered by Groq API + LLaMA-3.3 Upload, summarize, and interact with documents using an elegant Gradio interface. Supports intelligent summarization, key insights extraction, and natural question answering across PDF, DOCX, and TXT files.

Built an intelligent document summarization and question-answering system using Retrieval-Augmented Generation (RAG) with LangChain and Google Gemini 2.5 Flash, enabling accurate, context-aware understanding of large documents. 🤖 AI-Powered Document Summarization & Q&A Python · LangChain · Gemini 2.5 Flash · HuggingFace · ChromaDB

Smart Archive is an AI-powered document management system built with FastAPI, PostgreSQL, and Next.js. Upload, organize, and intelligently search documents using natural language and semantic AI — with automated summarization, tagging, and Q&A support.

elugu Intelligent Surveillance & Q&A System A CPU-friendly, privacy-focused surveillance and analytics system designed for Telugu: Motion-triggered audio/video capture (via Raspberry Pi Pico W MQTT or local webcam). Telugu ASR (Automatic Speech Recognition), Indic summarization, and visual people analytics (counts, gender, clothing).

A production-quality Retrieval-Augmented Generation (RAG) system that transforms how you interact with documents. Built with LangChain, ChromaDB, and Streamlit, this intelligent document assistant enables natural language Q&A, summarization, and multi-document comparison. All with source citations to prevent hallucinations.

Built an intelligent web app for automated PDF processing and smart querying. Features include user auth, text extraction, summarization (BART), Q&A generation (T5), and an AI chatbot (LLaMA 3 via Groq API). Integrated keyword-based relevancy and feedback system.

Notebook AI is an intelligent notebook system that turns personal notes, tasks, and daily logs into structured, AI-readable knowledge. It enables contextual Q&A, summarization, and habit insights directly from user data, designed to evolve into a personal AI agent with long-term memory.

AI Document Studio is an intelligent document processing and analysis platform that combines cutting-edge artificial intelligence with multi-format document support. The system leverages Google's Gemini AI to provide semantic search, automated summarization, study material generation, and interactive Q&A; capabilities

An AI-powered Project & Task Management System built with the MERN stack and Gemini AI. It features project tracking, Kanban-style task boards with drag-and-drop, and intelligent AI assistance for task summarization and Q&A — helping teams manage work efficiently and smartly

Built an intelligent Q&A system using LangChain, RAG, and Groq. Retrieves and summarizes answers from Wikipedia and arXiv with lightning-fast LLMs. Combines semantic search with real-time context retrieval for accurate, explainable responses.

AI-powered Legal Document Summarizer & Q&A Chatbot ⚖️ An intelligent system that summarizes Indian legal judgments and answers queries from uploaded case PDFs. Built using InLegalBERT, FLAN-T5, FAISS, and Gradio, it helps users quickly understand case facts, arguments, and decisions extracted from IndianKanoon.org .

🎥 YouTube AI Agent: Intelligent video summarization and Q&A system using RAG (Retrieval-Augmented Generation). Extract transcripts from YouTube videos and ask questions about content using LangChain, FAISS, and OpenAI. Built with Streamlit for an interactive web experience. Supports multiple languages including English and Hindi.

This project implements an intelligent e-learning platform where users can upload or access e-books, read them with integrated AI-driven tools, and test their understanding through automatically generated assessments. The system leverages NLP models to provide summarization, keyword extraction, question generation, and contextual Q&A.

ClauseEase AI is an offline, AI-powered Document Intelligence System developed as part of the Infosys Springboard Virtual Internship. It uses a locally hosted LLaMA 3 model via Ollama to deliver fast and secure PDF/TXT extraction, language detection, intelligent chunking, summarization, translation, and document-grounded Q&A. Built with Streamlit,

conversational PDF Q&A assistant powered by RAG and a multi-tool AI agent. You load any document, and the system intelligently routes your query to the right tool: answering questions, summarizing content, searching by keyword, or mapping out main topics Automatically.