Shrink and after-hours security in dark stores
· Updated · Slinai
Key facts
| Day clock | High-value cages, bag anomalies, exit exceptions |
|---|---|
| Night clock | Armed/disarmed doors, after-hours motion |
| Hub range | 30–50% shrink reduction with clip-led workflows — validate |
| Solution | Loss prevention + physical security |
| Retail cousin | Retail loss prevention AI on existing cameras |
Dark stores do not have a shopper “browse.” They have totes, cages, and a shutter at 2 a.m.
This is not pick-pack SLA and not order accuracy. It is loss and intrusion on existing CCTV. Slinai uses Video AI and video alarms. Homes: loss prevention and physical security. Hub: dark stores.
Two clocks, two WhatsApp groups
Peak clock: high-value cages, irregular bags at rider bay, exit without a matching dispatch.
Night clock: door after disarm, loitering at the shutter, staff-only hours.
Hub copy cites 30–50% shrink reduction with incident-led monitoring. That requires a reviewer, not a louder NVR.
What to detect (and what not to claim)
- Restricted-zone entry (pharma-adjacent, high-value).
- Bag handling that does not match a staged order — lead, not verdict.
- After-hours motion with clip to security.
- Not “who stole SKU 14” from pixels alone.
Compare vendors on compare and the buyer’s guide: your footage, false-positive story, existing cameras.
How this ties to Slinai
- Retail LP for the evidence culture
- Cluster: accuracy, cold chain
- Book a demo with one cage camera and one door camera
Common questions
Is this the same as retail shoplifting AI?
Same evidence idea, different layout — no public shop floor. Cages, rider bags, and night doors dominate. Read the retail LP guide for stores.
Can AI prove theft?
No. It produces leads and clips. Policy and people close the case. Do not auto-accuse.
What shrink reduction is claimed?
Hub copy cites 30–50% shrink reduction with incident-led monitoring. Treat as a programme range when process exists — not a guarantee.
After hours vs peak shrink?
Both. Peak hides in bags and exits. Night is the door. Split alert routes so ops and security do not share one noisy group.
Facial recognition?
Not required. Slinai default is behaviour and zones.
Related pages
Guides in this cluster point to live product, industry and use-case pages.
Related guides
Cold chain and FEFO rotation on dark store cameras
Dark store cold-chain and FEFO analytics flags door-open dwell and shelf-rotation drift on existing CCTV — process evidence, not a logger replacement.
Dark store order accuracy and defect prevention
Dark store order-accuracy analytics flags rushed pack, skipped QC and process drift on existing CCTV — a complement to WMS scans, not a replacement.
Dark store rider-bay handoff: the last 90 seconds of SLA
Dark store rider-bay analytics times queue depth, unattended bags and delayed handoffs on dispatch CCTV — the last 90 seconds after pick is already on time.