Fig 01
Connect
Existing cameras come first.
Private Vision connects to the installed environment instead of requiring replacement.
System Architecture
How Private Vision works in practice.
The flow is straightforward: connect to existing camera streams, process video locally, detect and track meaningful activity, then organize everything into a searchable incident layer.
No rip-and-replace. No mandatory cloud dependency. The intelligence layer is designed to slot into existing camera environments and add structure immediately.
Five-Step Flow
System flow from camera to incident review.
1
Connect to cameras.
Connect existing IP cameras and NVR streams over RTSP. ONVIF-compatible devices are recommended for cleaner interoperability.
2
Process video locally on Mac hardware.
The local intelligence engine runs on a Mac mini, Mac Studio, or equivalent Apple Silicon device on the same LAN.
3
Detect and track objects.
Identify people, vehicles, packages, and animals in real time while preserving camera, zone, and timestamp context.
4
Build the structured event timeline.
Convert activity into a readable incident record so review starts with events, not an unbroken recording.
5
Generate summaries and enable search.
Make the final dataset usable through grounded AI summaries, clip references, and natural-language search across the event index.
Simple Diagram
Text description of the system diagram.
- Left column: existing cameras and NVR feeds on the local network
- Center block: Private Vision local intelligence engine on Apple Silicon hardware
- Right column: event timeline, search interface, summaries, and clip review
- Bottom note: no mandatory cloud dependency for core analysis workflow
Core Components
Input
RTSP streams / ONVIF devices
Existing system
Processing
Local inference engine on Mac hardware
On-site
Output
Timeline, summaries, search, clip links
Web dashboard
Figure Sequence
Three views of the workflow.
The system can be explained simply to clients and operators: connect the feeds, process locally, then review intelligence instead of raw footage.
Fig 02
Process
Inference stays local.
Object detection, tracking, and indexing run on dedicated Apple Silicon hardware.
Fig 03
Review
Operators review events, not recordings.
Summaries, search, and timelines help users move faster with less manual review.
See the workflow with your own install model in mind.
We can walk through camera connectivity, local hardware sizing, and how the timeline and search experience fits into real deployments.