The Omni-Vision protocol allows the Demon Architect to utilize connected camera peripherals (webcams, mobile cameras via Neural Link) to analyze the physical environment. This is not just recording; it is active perception.
Computer vision detects objects and scenes to enhance user workflows with context-aware guidance. Local-first processing reduces exposure risks, and encrypted channels protect remote inference when necessary. Indicators display camera state transparently so users remain in control. Lightweight models enable responsive behavior on typical hardware while keeping resource usage modest. Combined with straightforward privacy controls, vision features deliver practical value without compromising safety.
Use cases include passive presence monitoring, context-aware UI hints, and high-level collaboration signals that avoid raw feed sharing. The system offers simple toggles to enable or pause features instantly. Logs capture event-level metadata for audits without sensitive data storage. Together, these choices produce an experience that is useful, fast, and respectful of privacy.
| Component | Details |
|---|---|
| Detection | Efficient models, NMS, confidence gating, stable outputs |
| Privacy | Local-first processing, encrypted remote channels, opt-in exposure |
| Performance | Adaptive frame rates, compact memory use, low-latency pipelines |
Do you store video? No, only high-level event metadata is recorded for audits.
Can I disable vision quickly? Yes, toggles pause features immediately and indicators show camera state.
Is remote analysis safe? Remote inference uses encrypted channels and respects explicit opt-in policies.
All visual data is processed locally or via secure encrypted channels to the configured AI provider. No video feed is stored on external servers without explicit user command. The "Eye" icon in the interface indicates when the vision system is active.