Privacy isn't a setting. It's the architecture.
We don't "promise not to look at your data" — the architecture simply gives your data no path off your computer. Moving AI back onto your own machine changes more than speed.
Where your data goes, in one diagram.
There are exactly two outbound connections, and neither carries your content. This isn't a policy promise — it's the code-level architecture, continuously verified by automated tests.
Six modules, local models and your data — all AI happens here.
To this system, the cloud is only a download source — never a destination for your data.
Cloud AI vs. Armor EdgeAI
| Typical cloud AI service | Armor EdgeAI | |
|---|---|---|
| Where data goes | Uploaded to the provider's servers | Stays on your computer, saved in place |
| Cost | Subscriptions or metered billing | Runs locally — no fees, no quotas |
| Offline | Everything stops | AI keeps working |
| Peak hours | Queues, throttling, slowdowns | Your GPU serves only you |
| Confidential files | Depends on the provider's terms | Never leave the machine — no third party to trust |
| Usage statistics | Telemetry collection is the norm | Zero telemetry, not a single record |
Three underlying reasons
Marginal cost ≈ 0
Download a model once; every inference after that uses your own electricity and GPU — the more you use it, the more you save.
Latency set by hardware
No network round-trips, no queues; response speed depends on your machine, not someone else's datacenter load.
Privacy as architecture
Data never leaves the machine, so you don't need to study processing terms to feel safe — there is no third party on the path.