Making existing cameras intelligent.
Most buildings already have cameras. Almost none of them have anything that understands what's in frame. QuantumSight is the layer that does — built on top of the CCTV that's already there.
The problem
Most buildings already have cameras. What they don't have is anything that understands what's in frame — so footage only matters after something has already gone wrong.
QuantumSight sits on top of existing CCTV — no rip-and-replace. An edge box runs vision models on the local feed and turns raw footage into events a security team can actually act on.
Four steps between a camera and something worth a person’s attention.
- 01Existing CCTV
Whatever's already on the wall. RTSP in, no new hardware on the camera side.
- 02QS AI Box
An edge device running vision models on the local feed. Nothing leaves the building unless it matters.
- 03Cloud inference
Heavier models and cross-camera context for the events that need a second look.
- 04Alerts dashboard
What a security team actually watches — events, not 40 live tiles.
Pipeline: existing CCTV → QS AI Box (edge) → cloud inference → alerts dashboard.
TODO — a paragraph on what you're building right now and what you've learned shipping it.
BUILT WITH — COMPUTER VISION · EDGE INFERENCE · PYTHON · REACT
Short notes from building in public. Newest first.
Have cameras that could be doing more?
We’re running early pilots. If you operate a site with existing CCTV and a security team that’s drowning in tiles, let’s talk.