A flexible, secure,
vendor-agnostic
knowledge platform.

Bring your documents, pick your stack, and turn them into an AI-powered knowledge engine with intelligent caching, enterprise-grade security, and full control over your data.

💬

What are the security policies for document access?

🤖

Based on your organization's documents, here are the key security policies...

What It Is

RAG Fortress is a plug-and-play Retrieval-Augmented Generation system with support for multiple LLMs, vector stores, embedding providers, and custom security layers. It features semantic caching for up to 80% cost reduction, message encryption at rest, and unified configuration for effortless provider switching.

Open source, local-LLM friendly, and production-ready with enterprise security. Build the RAG system you need, not the one a vendor wants you to use.

Why It's Not Just Another RAG Tool

🔌

Vendor Agnostic by Default

Choose your LLM, your embeddings, your vector store, and your database. Nothing is locked in.

🏠

Internal LLM Support

Local models via llama.cpp or any self-hosted provider. No document leaves your environment if you don't want it to.

🔒

Enterprise-Grade Security

HTTPOnly cookie authentication, message encryption at rest, automatic log sanitization, and multi-level security clearance enforcement.

⚡

Intelligent Semantic Caching

Multi-tier semantic cache reduces LLM API costs by up to 80% and delivers instant responses for similar queries.

🎯

Unified Configuration

Switch between LLMs, embeddings, and vector stores with unified settings. Supports hybrid search, fallback LLMs, and system diagnostics for complete control.

👥

Designed for Real Teams

User management, admin dashboard, optional error reporting, logging, and organization support.

Core Features

✓ Easy setup with environment-based configuration
✓ Document ingestion with multiple file formats
✓ Supports OpenAI, Gemini, Llama.cpp, and HuggingFace models
✓ Plug-and-play vector store integrations (Qdrant, Pinecone, FAISS, Chroma)
✓ Multi-tenant ready with department isolation
✓ Role-based access control (RBAC)
✓ Chat interface + search interface
✓ Admin controls for LLM config, embeddings, vector store
✓ Semantic caching with RedisVL for 80% cost reduction
✓ Message encryption at rest with optional cache encryption
✓ HTTPOnly cookie authentication & automatic log sanitization
✓ Hybrid search (vector + keyword) with configurable weights
✓ System diagnostics & health monitoring
✓ Unified configuration for effortless provider switching
✓ RESTful API endpoints for integration
✓ Document approval workflow
✓ Demo mode for public showcases

Who Benefits from RAG Fortress?

From developers to enterprises, RAG Fortress adapts to your specific knowledge management needs.

👨‍💻

Developers & Engineers

  • • Spin up RAG systems without vendor lock-in
  • • Experiment with different LLM architectures
  • • Build custom RAG solutions for clients
🏢

Enterprises & Businesses

  • • Secure internal knowledge base with RBAC
  • • Department-level access control
  • • Policy & compliance document management
🎓

Educational Institutions

  • • Course materials & lecture notes hub
  • • Student AI study assistants
  • • Research paper repository with semantic search
🔐

Security-Conscious Organizations

  • • 100% on-premise deployment with local LLMs
  • • Air-gapped environment support
  • • Multi-level security clearance enforcement
🌍

NGOs & Nonprofits

  • • Community knowledge systems
  • • Resource libraries without cloud costs
  • • Multi-language document support
⚖️

Legal & Compliance Teams

  • • Case law & regulation research
  • • Contract & agreement analysis
  • • Audit trail & activity logging

How It Works

1

Upload Documents

Add PDFs, text files, CSVs, and more to your knowledge base

2

Configure Providers

Choose your LLM, embeddings, and vector store

3

Index Content

Process and vectorize your documents

4

Start Querying

Ask questions and get context-aware answers

See It In Action

Experience the power of intelligent document conversations

💬 RAG Fortress Chat
RAG Fortress Chat Interface

Intelligent Conversations with Your Documents

Get context-aware answers powered by your knowledge base

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Natural Conversations

Chat naturally with your documents and get intelligent responses

🔐

Enterprise Security

HTTPOnly cookies, E2E encryption, log sanitization & RBAC

⚡

Lightning Fast

Semantic caching reduces costs by 80% with instant responses

🎯

Context-Aware

Understands your documents and provides relevant answers

🤖

Multiple LLMs

Support for OpenAI, Gemini, HuggingFace, and local models

📊

Activity Tracking

Complete audit trails and analytics dashboard

Complete Platform Overview

Admin Dashboard

Admin Dashboard

Activity monitoring & analytics

Application Settings

Application Settings

Configure LLMs & vector stores

Department Management

Department Management

Organize teams & access control

User Invitations

Multi-Tier Invitations

Email-based user onboarding

Activity Logger

Activity Logger

Detailed audit logs

Settings Details

Detailed Configuration

Fine-tune every setting

Quick Start Guide

Get RAG Fortress running in minutes with our streamlined setup process.

🔧 Backend Setup
# Clone repository
git clone https://github.com/nurudeen19/rag-fortress.git
cd rag-fortress/backend

# Install with uv (recommended)
uv sync

# Activate environment
.venv\Scripts\Activate  # Windows
# source .venv/bin/activate  # macOS/Linux

# Configure environment
cp .env.example .env
# Edit .env with your API keys

# Initialize database
python setup.py

# Start server
python run.py
🎨 Frontend Setup
# Navigate to frontend
cd frontend

# Install dependencies
npm install

# Configure environment
cp .env.example .env
# Set API_URL if needed

# Start development server
npm run dev

# Access at:
# Frontend: http://localhost:5173
# Backend: http://localhost:8000
# API Docs: http://localhost:8000/docs

Ready to Build Your Knowledge Platform?

Start building with RAG Fortress today. Open source, flexible, and built for teams.