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
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.
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.
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.
Repository for DevVault AI web application.
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.
Chat with your PDF documents using RAG. Built with LangChain, FAISS vector store, Groq LLM, and Streamlit. Every answer cites its source.
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
Transparent Retrieval-Augmented Generation (RAG) system built with Flask, Gemini, FAISS, and SQL Server that visualizes every AI retrieval step in real time.
A Django RAG workspace for cited document chat, retrieval, feedback, and evaluation.
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.
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.
Basic RAG document question-answering system for local text files.
SecAI is a fully local AI assistant with Retrieval-Augmented Generation (RAG), built using FastAPI, React, PostgreSQL, ChromaDB, Ollama, and Docker. Upload documents, chat with a local LLM, and get cited answers from your own files. Privacy-first, no cloud APIs, no external dependencies, and fully self-hosted.
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