Unmanned stores

Automated anomaly detection for unmanned stores

How AI automatically detects every anomaly in an unmanned environment, from intrusion and damage to refrigeration faults.

Request a consultation

Signals to read first

Three signals to read before the result

Cannot handle varied anomaly types individually

Theft, facility issues, and safety risks are different anomaly types, making it difficult to cover them with one operational response.

Night and dawn blind spots

Nobody is watching during the late-night hours when issues can be most persistent. A problem may continue for several hours.

Live preview

This is what you actually see

01 Detect · saai care

Simultaneous detection of multiple anomaly types

Independently detects suspect theft, open cooler doors, spilled items, excessive dwell, and after-hours intrusion. Allows customized notification recipients and response modes per anomaly type.

ⓘScreens are illustrative and may differ from the actual service.

Before · After

From finding the result later, to receiving the signal first

Knowing first

saai care · saai insight · saai agent

How AI automatically detects every anomaly in an unmanned environment, from intrusion and damage to refrigeration faults.

Simultaneous detection of multiple anomaly types
Anomaly event logs and statistical analysis
Automated response per anomaly type

Decision flow

Connect the evidence from signal to action

01 · 01 Detect · saai care

Simultaneous detection of multiple anomaly types

Independently detects suspect theft, open cooler doors, spilled items, excessive dwell, and after-hours intrusion. Allows customized notification recipients and response modes per anomaly type.

02 · 02 Analyze · saai insight

Anomaly event logs and statistical analysis

Aggregates daily and weekly anomaly counts, type distributions, and resolution times to guide operational improvements.

03 · 03 Act · saai agent

Automated response per anomaly type

Executes preset workflows automatically per anomaly type: cooler door left open → warning broadcast; intrusion → alarms + owner & security alerts; spills → staff notification.

Operational evidence

See the scene and the outcome together

Expected results

The range of anomalies that occur in unmanned stores

Unmanned stores face more than theft: a refrigerator door can remain open, a product can fall into a walkway, or a customer can linger for a long time after drinking. Without staff on site, these situations cannot be discovered immediately.

-82%

Anomaly discovery delay

5가지

Anomaly types detected simultaneously

24시간

Uninterrupted automatic monitoring

* Figures are illustrative examples of real deployments. Actual results vary by site.

An evening unmanned-store scene with an anonymous visitor leaving — Operational context image · not an actual analysis screen

Case studies

See how it worked in a similar environment

View case studies

How three products help this space together

Detect, analyze, and act connected in one continuous operating loop.

Detect

saai care

Detects critical anomalies in real time.

saai care Learn more

Analyze

saai insight

Analyzes why it happened and reveals trends.

saai insight Learn more

Act

saai agent

Proposes next actions by priority; a person confirms.

saai agent Learn more

View all solutions Unmanned stores industry detail

103 patents
SOC 2 · PIPA certified
1,700+ cameras connected
8+ partner brands

Could this work in your space too?

Tell us about your current CCTV setup and space. We will review a practical starting point with you.

Request a consultation