Busy floors hide risk
Staff attention is split across aisles, checkouts, entrances, and storage areas, so unusual activity can blend into normal movement.
Retail CCTV Video Analytics
Turn Retail CCTV Into Real-Time Security Alerts
AIn-Guard analyses live video feeds from your existing cameras and detects unusual or suspicious behaviour, such as concealment actions. When an event is detected, the system sends a short video snippet to authorised staff in real time.
Compatible with CCTV workflows No Camera Replacement Required Built for retail teams GDPR aware setup
Suspicious Detection in Shelf 2
AIn-Guard is tested in selected locations in Austria and Germany. The system analyses live camera feeds and flags behaviour such as unusual movement or possible concealment actions. When an event is detected, AIn sends a short video snippet like that one to authorised staff in real time.
THE PROBLEM WITH TRADITIONAL CCTV
CCTV records everything. Critical footage often goes unseen.
Traditional CCTV creates more footage than teams can realistically monitor. Important moments often stay buried in hours of recordings.
AIn-Guard changes that by turning passive cameras into real-time event detection .
Review happens after the incident
Footage is usually checked only after something has happened. By then, the chance to react in real time is gone.
Footage search is slow
Finding the right moment by hand takes time, creates delays, and makes incident review harder to prioritize.
Solution
How AIn-Guard Works
AIn-Guard monitors live camera activity, detects unusual movement patterns, creates reviewable alerts, and notifies authorized staff so incidents can be reviewed in real time.
How the intelligence layer works
Analyze movement over time
AIn-Guard analyzes live camera streams by extracting human skeletal movement data. These movement patterns are compared with our machine vision model to identify suspicious behaviour.
Focus on movement, not identity
AIn-Guard does not use Biometrics. It analyzes skeletal movement data from live camera streams to detect posture, movement, stopping, turning, and concealment-like actions that may require staff review.
Flag suspicious movement for review
AIn-Guard identifies movement patterns that may indicate concealment-like or unusual behavior, then sends the relevant moment to authorized staff as a reviewable alert.
From camera to staff review
Connect existing cameras
Choose store zones
AIn-Guard analyzes camera streams
AIn-Guard flags suspicious behavior
Notify authorized staff
Measurable impacts using AIn-Guard*
AI-powered video analytics improve store profitability, enhance staff experience and minimize losses.
Up to 34%
Shrinkage Reduction
Store performance increases through reduction of losses detected by AI-powered monitoring systems.
Up to 92%
Detection Accuracy
AIn-Guard identifies suspicious behaviour with 87-92% accuracy in real-life environments.
From 3 Months
Potential Payback in High-Loss Locations
In stores with high shrinkage or frequent incidents, AIn-Guard may support faster payback helping teams detect and review suspicious actions in real time.
Response Time
AIn-Guard
Traditional Measures
3–5 min
012345
Minutes
Cloud-based alerts are delivered within 15–30 seconds, compared to 3–5 minutes with traditional footage review.
Respond up to 600% faster than traditional measures*The presented KPIs are derived from internal case studies and industry benchmarks. They do not constitute a guarantee of performance. Outcomes will depend on individual deployment conditions and operational execution.
Store coverage
Coverage for the Retail Zones That Matter
Focus review attention on the store areas where shrinkage risk is highest, including entrances, aisles, blind spots, high risk shelves, small item shelves, and after-hours movement.
Entrance
Aisles
Blind Spots
High Risk Shelves
Small Item Shelves
After-Hours Areas
Coverage Frame
Zones that matter in retail
Entrances and exits
Watch the points where movement starts and ends so activity is easier to review in context.
High risk shelves
Focus attention on shelves where small, high margin items are easier to conceal and harder for staff to watch continuously.
High Risk
Small item shelves
Highlight movement around shrinkage prone product areas such as supplements, medicine, protein bars, coffee, cosmetics, and other compact goods.
After-hours movement
Flag unusual movement during low activity hours, closing periods, or times when selected retail zones should be quiet.
Camera Compatibility
Works With Existing Camera Systems
AIn-Guard is built to fit into the camera and recorder setups many retail teams already use, without pushing a full replacement project.
CCTV and analogue upgrades
RTSP and ONVIF support
NVR and VMS deployments
Single-site or multi-site retail
Before setup
We review camera type, recorder access, stream availability, and site layout before connecting AIn-Guard.
Camera Stack No Replacement Push
Compatibility check
Before setup, AIn-Guard reviews the current camera stack, recorder setup, stream access, and site layout to confirm what can be connected.
CCTV / analogue Camera type reviewed
RTSP / ONVIF Stream access checked
NVR / VMS Recorder setup reviewed
Existing site setup Store layout considered
No replacement required
The goal is to connect what already exists where possible, not force a new camera system.
Designed around a practical check of the existing setup before the demo.
Deployment
Deployment Options That Match the Site
Choose the rollout that fits the site, whether the team wants faster launch, local control, or a hybrid setup.
EU Native Cloud
Cloud deployment where customer data stays within the EU, built for fast launch, remote access, and easier coordination.
Best for data residency
Local Edge
On-site processing close to the camera system, with no external internet required for local operation.
Best for local control
Hybrid
Local edge processing with cloud notifications, remote review, and multi-site visibility.
Best for connected retail chains
Privacy
Privacy-Aware Security Controls
Configure access control, retention periods, and review workflows to help stores use camera-based security alerts in a controlled, privacy-aware way.
Role-based access
Limit who can access alerts, camera views, and incident details.
Retention periods
Support defined retention periods for alerts, review records, and related footage references.
Human-in-the-loop
AIn-Guard supports staff review and does not make legal, disciplinary, or enforcement decisions automatically.
No biometric identification
AIn-Guard is focused on event detection and review, not facial recognition, biometric identification, or person identification.
Designed to support controlled access, defined retention periods, human review workflows, and no biometric identification.
AIn-Guard is designed to support GDPR-aware security workflows. Final compliance depends on each store’s configuration, legal basis, signage, policies, and local requirements.
AIn-Guard
Demo / onboarding
Book a Retail Security Demo
Tell us about your business, camera count, and locations so we can check where AIn-Guard fits best.
Takes less than 1 minute
It helps us check basic camera compatibility before the call.
What this covers
Business type, camera count, locations, and contact details.
FAQ
Questions Retail Teams Ask Before a Demo
Answers to the most common questions about using AIn-Guard with existing CCTV systems, staff workflows, and compliance requirements.
Need a site-specific answer?
Book a demo and we can review your camera setup, store zones, and alert workflow.
Request a demoCan AIn-Guard work with existing cameras? + -
Yes. AIn-Guard is designed to work with existing CCTV setups where camera access and video stream compatibility are available.
Does AIn-Guard replace security staff? + -
No. It supports staff by highlighting moments that may need review. Final decisions should stay with authorized people.
Does AIn-Guard use facial recognition? + -
No. The system should focus on movement patterns and unusual activity, not identifying people by face.
How does AIn-Guard support GDPR-aware workflows? + -
AIn-Guard is designed to support privacy-aware security workflows with access controls, retention rules, human review, and deployment notices. Final compliance depends on each store’s setup, legal basis, policies, and local requirements.
Can AIn-Guard be used in Germany and Austria? + -
Yes, but deployment should follow local workplace, privacy, and CCTV rules. The system should be configured to avoid unnecessary monitoring.