Secure AI conversations with documents, video, audio, and more. Personal workspaces for focused context, group spaces for shared insight. Classify docs, reuse prompts, and extend with modular features.
Private, self-hosted document chat for attorneys: parse legal PDFs and query them with local open-source LLMs (Ollama) + verifiable page citations. One-click desktop app at docuchat.app.
Local NotebookLM alternative for private document analysis, local RAG, document chat, and AI report exports
InsightDocs AI is a Streamlit-based web application that enables users to upload PDF documents and engage in conversational interactions with them using Retrieval-Augmented Generation (RAG) powered by Google's Gemini AI. Key features include PDF processing, AI-driven chat capabilities, intelligent document retrieval via FAISS vector search.
Built an AI-powered Enterprise Document Intelligence Platform that supports multi-format document ingestion, semantic search, RAG-based conversational querying, AI summarization, compliance analysis, and agentic workflow automation using FastAPI, vector databases, and Generative AI models.
Repository for DevVault AI web application.
A local RAG application that lets users upload documents and chat with them using FastAPI, LangChain, ChromaDB, Ollama, and a ChatGPT-style Next.js frontend.
Un sistema RAG per chattare con documenti locali usando Foundry e modelli LLM su CPU
A professional-grade RAG (Retrieval-Augmented Generation) platform for secure document intelligence. Chat with your documents (PDF, DOCX, PPTX) using Google Gemini and Qdrant. Features multi-strategy retrieval, admin analytics, and a premium Gradio interface
Chat with your PDF documents using RAG. Built with LangChain, FAISS vector store, Groq LLM, and Streamlit. Every answer cites its source.
A fully offline, self-hosted, enterprise-grade AI Knowledge Assistant. Securely chat with PDFs, DOCX, and Markdown documents using local LLMs (Ollama) and hybrid vector search (FAISS + BM25). Zero cloud API dependencies.
A modular, plugin-based Retrieval-Augmented Generation (RAG) framework for building document-aware AI applications with interchangeable loaders, vector stores, retrievers, and LLM providers
ChatApplication — Document chat and handbook generator using Gradio, LightRAG, Supabase pgvector, and OpenRouter.
DocuMind is a RAG-powered chatbot that lets you upload PDFs/documents and chat with their content using vector search and LLM generation. It features source citations, token usage tracking, and a clean dark-themed interface for intelligent document interaction.
An AI-powered RAG application built with LangChain, Groq, HuggingFace Embeddings, ChromaDB, and Streamlit that answers questions from PDFs, DOCX, TXT, Websites, and YouTube videos.
Transparent Retrieval-Augmented Generation (RAG) system built with Flask, Gemini, FAISS, and SQL Server that visualizes every AI retrieval step in real time.
AI-powered Retrieval-Augmented Generation (RAG) document assistant built with Ollama, LangChain, ChromaDB, Sentence Transformers, and Streamlit.
Basic RAG document question-answering system for local text files.
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