Retail in Malaysia runs on thin margins and fast-moving customer behaviour. Acta combines computer vision, edge AI and connected sensors so store teams can see footfall, queue pressure, shelf availability and conversion the way an e-commerce team sees a website.
The challenge
- Footfall and conversion measured manually, or not at all
- Out-of-stock shelves discovered only after the sale is lost
- Queue build-up at peak hours with no early warning
- Cold chain and store environment logged on paper
Outcomes
- Staffing rosters matched to real hourly demand
- Faster shelf recovery and fewer lost baskets
- Objective comparison between outlets and campaigns
How Acta delivers
01
Anonymous vision analytics for entry counts, dwell time and zone heat
02
Shelf and planogram monitoring with automated replenishment alerts
03
Queue detection that pages staff before the line becomes a complaint
04
Wireless temperature and humidity monitoring for chillers and back-of-house
05
One dashboard consolidating every outlet, comparable store to store
Technology stack
Edge AI cameras with on-device inference
LoRaWAN / NB-IoT environmental sensors
IoT Systems device management platform
Retail analytics APIs into existing POS and ERP
Related industries
Want this applied to your site? Send us the operational problem and we will propose an architecture.
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