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AI Technology
Term Definition

Edge AI

Analyzing video right on on-site hardware, without sending footage outside

Core Definition

Edge AI runs AI analysis on compact on-site hardware (edge devices) instead of cloud servers. Footage never leaves the store, reducing data-exfiltration risk, and processing stays real-time regardless of network conditions.

How this differs from the cloud

The cloud approach sends video to an external server for analysis. This incurs line costs and latency, and more importantly, means the original footage leaves the store. The edge approach brings the analysis to where the data already is: the footage stays in place, and only the results move.

Real-time performance differs too. Analyses where seconds matter, such as crowd detection or anomaly alerts, are fastest when processed immediately on-site, without the round-trip time of network traffic.

The relationship with privacy

Edge AI naturally aligns with privacy by design. When footage is anonymized and analyzed in the device's memory and never stored, all that leaves the device is statistical values like coordinates and age brackets. The question of "where is the original footage" disappears entirely.

This is favorable from a regulatory standpoint too. Since data never crosses national borders or business premises, the review process around data transfer and outsourcing becomes much simpler.

How SAAI Uses It

DEEPINGSOURCE's default deployment is on-premise: a compact AI analysis device installed on site. The device receives existing CCTV footage and anonymizes and analyzes it in memory immediately, sending out only statistics with no personal information. The same structure scales from small stores with 4 to 8 cameras up to deployments of thousands of cameras.

See it in action

Real-World Application

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