I built a bootable Linux distribution that treats AI as a system primitive – like CPU or memory. Designed for security-conscious environments where data cannot leave the network.

The problem: Most AI requires cloud APIs, which means your data leaves your control. For banks, healthcare, defense, and regulated industries – that's a non-starter.

The solution: EdgeAI-OS runs everything locally. No cloud calls. No API keys. No telemetry. Boot the ISO, use AI. Your data never leaves the machine.

Security features: - 100% offline operation – air-gap friendly, zero network dependencies - No external API calls – all inference runs locally on CPU - Command risk assessment – every command classified as Safe/Moderate/Dangerous - Dangerous pattern blocking – prevents rm -rf /, curl|bash, fork bombs, etc. - Open source & auditable – MIT licensed, inspect every line of code - No data exfiltration – nothing phones home, ever

What's in the ISO: - Local LLMs (TinyLlama 1.1B + SmolLM 135M) – runs on CPU, no GPU needed - ai-sh: natural language shell where 80% of queries resolve instantly via templates - Multi-tier routing: simple queries → fast model, complex → larger model

Example ai-sh session: what time is it? [template] date ← instant, no LLM

files larger than 1gb [template] find . -size +1G ← instant, no LLM

rm -rf / [DANGEROUS] Blocked ← security check

configure nginx as reverse proxy [ai-generated] ... ← uses local LLM (~1-2s)

Target use cases: - Air-gapped enterprise environments (banks, healthcare, government) - Defense & classified networks - Edge devices with no internet connectivity - Privacy-conscious developers - Compliance-heavy industries (HIPAA, GDPR, SOC2)

Built with Rust, based on Debian. 4GB RAM recommended.

GitHub: https://github.com/neuralweaves/edgeai-os ISO Download: https://github.com/neuralweaves/edgeai-os/releases (1.2GB)

Would love feedback, especially from anyone working in secure/regulated environments. What features would make this enterprise-ready for you?