Case study using dotfurther's Open Discover Platform with the RavenDB document store to rapidly create a full-text search/eDiscovery/information governance capable demonstration application.

RAG-Ingest: A tool for converting PDFs to markdown and indexing them for enhanced Retrieval Augmented Generation (RAG) capabilities.

A simple RAG toolkit.

An implementation of the GraphRAG pipeline (based on the 2024 paper "From Local to Global" by Edge et al.) for query-focused summarization of large text corpora.

Self-hosted RAG engine for AI coding assistants. Ingests technical docs & code repositories locally with structure-aware chunking. Serves grounded context via MCP to prevent hallucinations in software development workflows.

Self-hosted RAG prototype to ingest PDFs/HTML and chat with them via a local UI

An AI Analytics Dashboard for research labs analytics, collaboration, and email workflow using React and FastAPI.

Store millions of text chunks inside ultra-compact MP4 files, index them with local embeddings, and retrieve answers instantly for fully offline RAG with any LLM.

Async document watcher that keeps your RAG index hot. Automatically ingests new or changed documents into a live RAG pipeline with built-in observability.

Agentic-RAG-Chatbot-MCP implements a multi-agent chatbot leveraging Retrieval-Augmented Generation (RAG) to interact with diverse document types. The system maintains a persistent knowledge base, supports multi-turn conversations, and allows users to upload documents for contextual, accurate responses. Built with Streamlit and Python.

AI-powered RAG assistant for parents to quickly find information on Brainwonders’ career counseling programs, pricing, and services; combines curated knowledge base with NLP.

ScriptumAI is an advanced Retrieval-Augmented Generation platform designed for document ingestion and query processing.

🗂️ Build a knowledge graph for global query-focused summarization from document corpora using the GraphRAG pipeline, enhancing information synthesis.

📊 Streamline query-focused summarization by constructing knowledge graphs and extracting insights from document corpora with the GraphRAG pipeline.