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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.
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.
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