educational

A Hands-On Review of AI Camera Monitoring for Retail

A Hands-On Review of AI Camera Monitoring for Retail

Last month, I outlined the main AI-powered loss prevention options available to businesses: DIY solutions, hosted services and enterprise platforms. This time, I decided to test one out myself. I contacted a cloud video platform that integrates with Lightspeed POS and scheduled a demo.

I wanted to know whether the technology really delivers on the marketing claims. Even more importantly, I wanted to find out exactly how difficult it might be for me — or you — to actually implement AI-powered loss prevention.

If the system saves your managers a few hours of investigation each week, detects one theft you would have missed or shields you from a single liability claim, it pays for itself.

Here’s what I learned.

A Trio of Convenient Features
As the vendor rep shared their screen and guided me through a live retail setting, three very useful functionalities stood out most:

  • Motion search with zone filtering. With this feature, you draw a line on the screen — across a doorway, around a display case, or anywhere else — and the system filters to show you only footage where someone crossed that line. Instead of scrubbing through eight hours of video, you’re watching a two-minute highlight reel of relevant events. This alone could save hours during an investigation.
  • Natural language search. The rep typed “person with backpack” and the system retrieved clips of customers matching that description across multiple cameras. It’s not perfect — lighting and camera quality definitely matter — but once again, it’s significantly faster than manual review. For retailers dealing with repeat offenders, this is a potential game-changer.
  • Transaction-to-video linking. This is where POS integration really proves its value. Every transaction — each void, discount and refund — is automatically time-stamped and associated with the relevant video. You can also filter by employee and view a staff member’s transactions in order. No more sifting through footage trying to match receipts to time stamps.

Adult retail establishments that also manage admission-based revenue to a theater or arcade may find this last feature helpful for reconciling entries with register sales, since the system can identify discrepancies between foot traffic and transactions.

Implementation: Simpler Than I Expected
I went into this prepared for a complicated infrastructure discussion about cameras, the protocols they support and maybe having to rewire everything.

The reality turned out to be refreshingly simpler. If your cameras support ONVIF — a  standard protocol most IP cameras from the last decade support — integration is easy. The platform finds your cameras automatically. But even if you have older analog cameras running over coaxial cable, you don’t need to replace them. An encoder converts the analog signal to digital.

The platform also replaces your existing DVR with a new recording device. Your footage remains stored locally with standard retention periods — typically 30 days in HD and another 30 days at lower resolution — along with optional cloud backup for disaster recovery. If the device fails, the vendor assured me, a replacement is included in the subscription, eliminating the need to purchase new DVRs out of pocket every few years.

Self-install is an option here if you’re comfortable with basic networking. Plug in the device, connect it to your router and follow the setup wizard. For retailers who have installed their own routers or configured a network-attached storage device, this will be familiar territory.

The Numbers
I received a quote for eight cameras and the full feature set, on a month-to-month commitment. Here’s the breakdown:

  • Base subscription including device, software and support: $198.
  • Analog encoder for legacy cameras: $25.
  • AI analytics package with motion search and person tracking: $60.
  • Optional professional alarm monitoring: $60.
  • Optional 1TB cloud backup: $30.

The total for all features: $373 per month, with POS integration included at no extra charge. The contract is month-to-month after an initial 30-day term — no multi-year commitment; cancel anytime. For multi-location operators, cloud storage is pooled together at reduced rates.

So Is It Worth It?
The return on investment will vary based on your situation. If the system saves your managers a few hours of investigation each week, detects one theft you would have missed or shields you from a single liability claim, it pays for itself.

The stronger argument is operational. Instead of reactively reviewing footage after something bad happens, you’re developing proactive pattern detection. You can systematically audit employee transactions. You can monitor repeat visitors across locations. You can answer, in minutes, questions that used to take hours to resolve.

If you’re considering AI-powered loss prevention, here’s the practical path forward for determining whether a given solution suits your needs:

  • Know your cameras. Take pictures of your equipment. Most vendors can determine from photos whether you need an encoder or if your cameras will work directly.
  • Request a demo. Any reputable platform will guide you through their system. Watch for search speed, how transactions connect to video and whether the interface makes sense to you.
  • Get a quote based on your actual setup. Pricing depends on camera count, retention needs and optional features. Don’t assume — ask.
  • Look for month-to-month terms. The security industry favors short-term contracts. You shouldn’t have to commit to three years when you are likely to know sooner whether a solution works for you.

Your cameras have been watching all along. Maybe it’s time they started truly seeing. That being said, I’m not quite ready to declare victory based on a demo. Demos are designed to impress. The real test is deployment.

That’s why I will be running a pilot at our largest location after Valentine’s Day. I’ll report back with real-world results: How long did setup actually take? Did the AI search work as well with our camera quality as it did in the demo? Did we catch anything we would have missed? Did it change how we operate day-to-day?

Watch this space!

Zondre Watson is the general manager of technology and analytics for adult retail chain Ero-Tech. With a background in finance, chocolate and controlled chaos, he blends retail know-how with AI tools to keep 17,000 products moving smoothly.

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