Insight Engine: Your AI-powered document assistant. Ask questions, get answers, and citations instantly. Powered by local Llama 3 on Ollama for privacy and speed. No cloud, just pure local intelligence.

A simple yet powerful local AI Agent assistant that runs entirely on your machine. Option for remote LLM. Built for learning and deploy, Little MCP combines the power of open-source LLMs with advanced RAG that work with your personal documents. Included tools: real time weather, local documents RAG, local SQL database. Easy deploy your own agent.

Noto.ai is a local AI-powered PDF assistant that lets you chat with documents, ask questions, and get instant summaries—all offline using LLaMA 3 via Ollama. Built with Python and Kivy, it offers a clean desktop interface for students, researchers, and professionals who want to extract insights from complex PDFs efficiently and privately.

A privacy-focused AI tool built with DeepSeek 8B (via Ollama) and Retrieval-Augmented Generation (RAG). It processes unstructured documents, enabling semantic search and summarization using ChromaDB and LangChain. Features a Streamlit web interface for offline document uploads, queries, and results—ensuring security and efficiency.

PaperLens is a local, AI-powered paper reading assistant designed to support interactive scientific paper understanding. The system integrates document-grounded comprehension, scholarly metadata analysis, and contextual literature exploration within a unified reading environment, enabling users to go beyond linear PDF reading.

An AI-powered HR policy assistant built using Retrieval-Augmented Generation (RAG) to deliver accurate, context-aware answers strictly grounded in official company HR documents. This system ingests HR policy PDFs, converts them into vector embeddings, and retrieves only relevant policy sections before generating responses using a local LLM.

🚀 slackAgent: Your AI-powered Slack assistant! Built with LlamaIndex, ChromaDB, and OpenAI embeddings, it delivers instant answers from your documents via a sleek Slack bot or Streamlit web UI. Automate workflows with n8n, expose local APIs with ngrok, and query with ease using FastAPI. Join the future of intelligent chatbots! 🤖💬

AI-powered medical assistant using RAG architecture and local language models to answer diagnostic questions from clinical documents.

DocuVision AI – Multimodal RAG-powered document assistant that extracts text and images from PDFs and enables natural language querying using local LLMs.

AI-powered restaurant menu assistant that searches across multiple pizzeria documents. Local-first solution with modern chat interface and real-time responses.

Detacomm CamAI Chat Bot – A Streamlit-based AI assistant that lets you chat with your uploaded documents using Groq-powered LLMs and local vector search (FAISS + HuggingFace embeddings).

This project is a local AI-powered document assistant that allows users to chat with any file (PDF, DOCX, TXT, MD). Built with open-source tools and privacy-first principles, it enables natural language interaction with your documents — no cloud, no API keys required.

Offline AI assistant with RAG using phi-3 and Flask UI. Local LLM with PDF/Text RAG—fast, private, and server-free. Smart document Q&A system running locally with phi-3. Flask-powered RAG app using local embeddings and Ollama. Self-hosted LLM with doc search and natural language queries.

A production-grade, AI-powered personal assistant that answers questions using your uploaded documents (PDFs, Markdown, JSON, etc.) with Retrieval-Augmented Generation (RAG). Built with Golang backend, Next.js frontend, Qdrant vector database, and AWS S3 storage. Fully Dockerized with LocalStack for local testing.

A Streamlit-powered AI assistant that lets you chat with your PDF documents. Trinity uses FAISS for semantic search, Ollama for local embeddings, and Groq's blazing-fast LLMs to deliver accurate, context-aware answers. Upload PDFs, ask questions, and get instant insights — all in your browser.

Sanjeevani - An AI Powered Healthcare App where patients can get preliminary guidance for their possible causes of symptoms in their local language via an AI assistant, book doctor appointments seamlessly based on their location and language preference, as well as analyze their medical documents such as lab reports to get a simplified explanation.

DocAI - A Local, Private Document Q&A Assistant A lightweight AI chatbot that answers questions directly from your PDFs, DOCX, and TXT files—no cloud APIs, no data leaks. Powered by Phi-2 (CPU-optimized LLM) and FAISS for semantic search, it’s designed for researchers, students, and professionals

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RAG-powered local AI assistant for answering questions from documents.

AI-powered enterprise document assistant with local LLM - no API costs!

A rag powered AI assistant for documents, using open sourece local models.

A local AI Assistant powered by RAG that lets you chat with your PDF documents using local LLMs.

NIARAD — Offline AI study assistant powered by local LLMs. RAG pipeline for documents. Zero cloud.

AI-powered document assistant with local processing capabilities. Features PDF chat, secure embeddings, and optional cloud AI integration.

Local AI-powered medical assistant using RAG, FAISS, Ollama & MCP for document-grounded clinical Q&A.

AI-powered study assistant that summarizes documents and generates quizzes using local LLMs (Ollama) and Streamlit.

PatchPilot — An AI-powered CLI assistant for analyzing, refactoring, and patching local code and documents using LLMs.

Local private AI assistant powered by FastAPI, Streamlit, FAISS, and TinyLlama with document search and chat capabilities.

RAG-Powered Document Assistant using Vertex AI's RAG Engine & Agent Development Kit (ADK) with a local GUI.

AI-powered document assistant using Flutter, Node.js, and RAG architecture to enable contextual search and analysis of financial documents with local LLMs.