Enclava

Confidential AI Platform for businesses

Enclava is a comprehensive AI platform that makes privacy practical. It provides easy to create openai compatible chatbots and API endpoints with knowledge base access (RAG). All in a completely confidential way through privatemode.ai

Key Features

• AI Chatbots - Customizable chatbots with prompt templates and RAG integration (openai compatible)
• RAG System - Document upload, processing, and semantic search with Qdrant
• TEE Security - Privacy-protected LLM inference via confidential computing
• OpenAI Compatible - Standard API endpoints for seamless integration with existing tools
• Budget Management - Built-in spend tracking and usage limits

Quick Start

Prerequisites

• Docker and Docker Compose
• Git
• privatemode.ai api key

1. Clone Repository

git clone <repository-url>
cd enclava

2. Configure Environment

# Copy example environment file
cp .env.example .env

# Edit .env with your settings
vim .env

Required Configuration:

# Security
JWT_SECRET=your-super-secret-jwt-key-here-change-in-production

# PrivateMode.ai API Key (optional but recommended)
PRIVATEMODE_API_KEY=your-privatemode-api-key

# Base URL for CORS and frontend
BASE_URL=localhost

3. Deploy with Docker

# Start all services
docker compose up --build

# Or run in background
docker compose up --build -d

4. Access Application

• Main Application: http://localhost
• API Documentation: http://localhost/docs (backend API)
• Qdrant Dashboard: http://localhost:56333/dashboard

5. Default Login

• Username: admin
• Password: admin123

Change default credentials immediately in production!

Documentation

For comprehensive documentation, API references, and advanced configuration:

docs.enclava.ai

Architecture

• Frontend: Next.js (React/TypeScript) with Tailwind CSS
• Backend: FastAPI (Python) with async/await patterns
• Database: PostgreSQL with automatic migrations
• Vector DB: Qdrant for document embeddings
• Cache: Redis for sessions and performance
• LLM Service: Native secure LLM service with TEE support

Services

Service	Port	Purpose
Nginx (Main)	80	Reverse proxy and main access
Backend API	58000	FastAPI application (internal)
Frontend	3000	Next.js application (internal)
PostgreSQL	5432	Primary database
Redis	6379	Caching and sessions
Qdrant	56333	Vector database for RAG

Configuration

Environment Variables

See .env.example for all available configuration options.

Support

• Documentation: docs.enclava.ai
• Issues: Use the GitHub issue tracker
• Security: Report security issues privately

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