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December 15, 2024
5 min read

Building Iris: A Local-First AI Assistant

How we built Iris, a privacy-focused AI assistant that runs entirely on your machine. No cloud dependencies, no data collection.

Noam Favier
Developer & Founder
Building Iris: A Local-First AI Assistant

Building Iris: A Local-First AI Assistant

In an era where AI services increasingly depend on cloud infrastructure, we took a different approach. Iris is built with a local-first philosophy—your data never leaves your machine.

The Challenge

Modern AI assistants require constant internet connectivity and send all your queries to remote servers. This creates several problems:

  • **Privacy concerns**: Your conversations are stored on company servers
  • **Latency**: Network round-trips add delay to every interaction
  • **Costs**: Cloud processing isn't free at scale
  • **Availability**: No internet means no assistant
  • Our Solution

    Iris uses local models and runs entirely on your hardware. Here's what makes it special:

    Privacy by Design

    All processing happens on your machine. We literally can't see your data because it never reaches us.

    Lightning Fast

    No network latency. Responses are instant because everything runs locally.

    Offline Capable

    Work anywhere—on a plane, in a coffee shop, or in your basement. Internet optional.

    Cost Effective

    Pay once, use forever. No subscription fees or API costs.

    Technical Architecture

    Iris is built with:

  • **Go** for the core engine (fast, efficient, cross-platform)
  • **Python** for ML model integration
  • **OpenAI API** compatibility layer for easy integration
  • The architecture allows you to swap models, customize behavior, and extend functionality without vendor lock-in.

    What's Next

    We're working on:

  • More model support
  • Better context management
  • Plugin system for extensibility
  • Mobile apps
  • Iris is currently in alpha. Join our waitlist to be among the first testers.

    AIPrivacyLocal-FirstOpen Source