Self-hosted RAG platform for AI document search across GitHub, Notion, Google Drive, local files, and web sources with citations.

PDFs you can talk to.

All your Zotero annotations in one place — filter, export with citations, and turn highlights into linked, searchable ideas. Plus grounded Q&A with clickable page citations.

AI-powered Retrieval-Augmented Generation (RAG) assistant that performs document chunking, TF-IDF based retrieval, cosine similarity ranking, and context-aware answer generation using Groq LLaMA 3.3. Features interactive retrieval visualization, chunk highlighting, document indexing, PDF export, and a modern responsive UI.

AI-powered document Q&A system with vector search

RAG document Q&A app — paste a URL or upload a PDF, ask questions, get cited AI answers

DocMind is an AI-powered document Q&A assistant. Users upload documents (PDF, DOCX, TXT, Markdown), then ask natural language questions and receive answers with exact page-level citations, backed by semantic vector search (RAG — Retrieval-Augmented Generation).

Querious – Chat with your documents using retrieval-augmented generation (RAG). Upload PDFs, ask questions, get grounded answers.

AI-powered document chatbot where users upload PDFs and ask questions, and the system answers using retrieval-augmented generation (RAG) with an LLM.

Zero-config, privacy-first document Q&A — local embeddings, BYOK

A NotebookLM-style RAG web app that lets users upload PDF, TXT, or CSV files and ask grounded questions using Gemini embeddings, Gemini generation, and Qdrant vector search.

Next.js RAG chatbot with streaming UI, OpenAI embeddings, and vector search over markdown docs.

Upload your company docs and let your customers get instant, accurate answers — 24/7, no human needed.

RAG-based PDF Q&A — ask questions, get cited answers with similarity scores.

Full-stack retrieval-augmented generation (RAG) system for intelligent document Q&A. FastAPI backend with OpenSearch hybrid search, Next.js UI with streaming responses, Ollama LLM support, and Telegram bot integration. Production-ready with Docker.

A React + TypeScript web app that lets users upload documents and chat with them using AI. Built with Vite, Tailwind CSS, and React Router. Deployed on Vercel.