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Open Source

Your Intelligent, Private AI Research Companion

Supercharge your research with a powerful AI assistant that respects your privacy. Upload documents, analyze content, and get insights - all while keeping your data under your control.

Power Your Research

Advanced AI capabilities with complete control over your data

Choose between 100% private local deployment or secure cloud integration. Built on ChromaDB for blazing-fast vector storage, ensuring complete data control and uncompromised privacy.

AI Flexibility at Your Fingertips

Seamlessly integrate with OpenAI, Anthropic, Gemini, or XAI. For ultimate privacy, run open-source LLMs locally via Ollama. Mix providers or go fully offline - the choice is yours.

AI-Powered Research Companion

Harness vector search and semantic understanding for deep insights. Our adaptive AI evolves with your research, providing intelligent analysis and connections across your entire knowledge base.

Experience full offline capability with Ollama. Leverage local embeddings and LLMs for uncompromised privacy and complete control over your AI operations.

Powered by TypeScript, React, Python, FastAPI, and ChromaDB. Fully open-source under Apache License Version 2.0 - customize, extend, and innovate to fit your unique needs.

Seamless Cross-Platform Experience

Enjoy native apps across macOS, Windows, and Linux. Consistent performance and interface, no matter your preferred operating system.

Join the Research Revolution

Experience the future of research with our open-source AI companion. Join researchers worldwide who trust Notate for intelligent, private, and efficient knowledge management.

System Requirements

Choose the mode that best fits your needs

Perfect for getting started with cloud-based AI providers

  • Python 3.12
  • 4GB RAM minimum
  • 2GB free disk space minimum
  • Any modern CPU

For complete privacy and offline capabilities with OLLAMA

  • 16GB RAM minimum (32GB recommended)
  • 2GB free disk space minimum (10GB+ recommended for local models and file collections)
  • Modern CPU (8+ cores recommended)
  • GPU with 8GB+ VRAM recommended
  • Python 3.12

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