Years ago, I was deeply involved in upgrading the security camera system at a store in Hawaii. The process took several months. We provided store diagrams, mapped out camera lines of sight, waited for quotes, then coordinated with a contractor to install everything. It cost thousands — and by the time I left that position, the system still wasn’t fully operational.
At my current company, we operate with a less advanced system and have 21 locations to oversee. It can be tedious to sift through hours of footage. If I know when a specific incident occurred, it’s easier, but if I need to review an entire day and compare it to transactions, it’s nearly impossible to monitor effectively for theft.
If your system catches even one major theft, you’ve already recouped your costs.
This is where AI-powered loss prevention comes in. These systems execute quickly and automatically the tasks I would otherwise have to do manually: scan footage, flag suspicious moments and match transactions to video. They also let me search with plain English queries like “person at the toy wall between 7 and 9 p.m.”
If you have faced similar challenges, the question today isn’t whether the technology exists, but which specific service makes the most sense for a store like yours.
The Real Cost of Shrinkage
The National Retail Federation estimates average shrinkage at around 1.4%. For a single location generating $2 million in annual revenue, that means about $28,000 vanishes each year due to a mix of external theft, internal theft, administrative mistakes and vendor fraud. For a store with narrow margins, that’s not just a rounding error — that’s the equivalent of a part-time employee’s salary.
While the precise breakdown in those figures varies by store, internal theft often accounts for a more significant portion than most owners like to admit. Small stores with limited staff are especially vulnerable because there are fewer eyes watching and less separation of duties.
AI loss prevention systems address this challenge from various angles. On the external side, they identify behavioral patterns such as shoppers lingering near high-value items, concealment movements or repeated visits by the same person. Internally, the real strength lies in POS integration: automatically connecting every transaction to video footage so you can review voids, refunds and discounts without manually searching through hours of recordings.
How AI Video Analysis Works
Traditional security cameras generally record everything, leaving any analysis up to you. Motion detection offers some help, but “something moved” accounts for about 90% of retail operating hours. It’s noise, not signal.
AI-powered systems invert this model. Instead of recording everything and hoping you’ll identify what matters, they analyze the feed in real time and highlight specific events. The core technology is computer vision: algorithms trained to recognize objects, people, behaviors and patterns.
This makes a big practical difference in how you interact with the system. Instead of scrubbing through timelines, you’re searching. Modern AI video platforms allow you to query footage the way you’d search the web: “person with backpack at front counter,” “someone reaching behind the display case,” “vehicle in the parking lot after midnight.” What used to take hours now takes minutes.
Loss prevention is the obvious use, but the same technology also boosts sales intelligence. These same systems can track foot traffic entering your store, providing an accurate conversion rate when combined with transaction data. Some platforms create heat maps that show customer flow patterns. That’s merchandising data that previously required costly dedicated sensors.
When it comes to implementing this technology, you have three options, each with real trade-offs in cost, complexity and capability.
Tier 1: Self-Hosted/DIY
If you’re comfortable with technology and want maximum control with minimal recurring costs, self-hosted tools like Frigate, Viseron or Kerberos.io can turn a small computer in your back office into an AI-powered video analysis system. You own the hardware and control the data. Your only ongoing cost is electricity.
Let’s be clear, however: These aren’t plug-and-play solutions. You’ll be configuring software, editing configuration files and troubleshooting when things don’t work the first time. In addition, DIY means no vendor support. When something breaks at 10 p.m. on a Saturday, you’ll be searching forums instead of calling a help desk. There’s also no native POS integration — if you want transactions linked to video, you’ll have to build that yourself or go without. If “Docker” and “YAML” sound like foreign languages, this tier probably isn’t for you.
If those things fall within your technical comfort zone, however, and you enjoy tinkering, the payoff can be substantial: minimal hardware investment with no recurring subscription, and your footage never leaves your network.
Tier 2: Hosted/SMB Services
Hosted services provide the same AI-powered search and analysis without the need to manage servers. You pay a monthly fee in exchange for someone else handling infrastructure, updates and support. Your cameras stream to their cloud, their algorithms perform the analysis and you view results through a web dashboard or mobile app.
Some examples: Eagle Eye Networks offers a feature called Smart Video Search, that supports natural language queries and over 4,000 camera models, including direct Lightspeed POS integration. CheckVideo emphasizes speed, claiming to cut search time by 90%. Spot AI uses a hybrid system with both local and cloud storage. Solink focuses specifically on linking transactions to video footage.
It is worth noting that vendor responsiveness can vary greatly. Some companies treat inquiries from a single location as a low priority. Remember: A vendor who won’t respond to presale emails is unlikely to provide excellent support when your system fails during your busiest weekend.
Tier 3: Enterprise LP Stacks
For the complete package, enterprise platforms like Sensormatic and Vaidio provide turnkey solutions designed for retailers with dedicated loss prevention staff, multiple locations and matching budgets. They focus on exception-based reporting, automatically flagging suspicious transaction patterns without requiring manual oversight. The integration depth connects directly to your POS, inventory management and, in some cases, access control.
For a retailer with only one location, this is probably excessive. But if you’re part of a larger chain or planning rapid expansion, these platforms are worth considering in the future.
Checking Compatibility and Running the Numbers
All these systems need to access video streams from your existing cameras. The good news is that most IP cameras made in the last decade support the necessary protocols: RTSP for streaming and ONVIF for interoperability.
To perform a quick compatibility audit, download the free ONVIF Device Manager, connect to the same network as your cameras and run a scan. You’ll find out which cameras are compatible in five minutes. If cameras don’t appear, you’re probably using older analog equipment or a proprietary system. Incompatible cameras mean either investing in hardware or waiting until your next upgrade.
If your stores have a dedicated network segment for security equipment, you’ll need access to that network. For multiple locations, repeat at each store, since camera systems installed at different times may differ.
Naturally, you’ll also want to consider pricing. The DIY tier has the simplest math: $200-400 for hardware, no subscription. If your system catches even one major theft, you’ve already recouped your costs. Break-even comes in just a few weeks.
Hosted services require different calculations. Let’s return to our original example: that single location generating $2 million in annual revenue. Assuming $30 per camera per month for six cameras, that’s $2,160 annually. Against $28,000 in shrinkage, you need roughly an 8% reduction in losses to break even. However, factoring in time saved on investigations — hours you can spend on revenue-generating activities — the real ROI is probably better than just shrinkage math alone.
Getting Started
Regardless of which tier you decide to go with, the implementation path looks similar:
- Begin with a small deployment. Install one or two cameras in the highest-risk areas.
- Define specific zones. Generic motion alerts are ineffective compared with zone-based detection for your key areas. Log every time someone visits the register.
- Establish a routine. Conduct a daily review of flagged events, weekly transaction audits and monthly pattern analyses.
- Track shrinkage results. Compare shrinkage before and after installation, and document any incidents you may have overlooked.
AI-powered loss prevention is now available at all price levels, and will work with most cameras from the past decade. The real question is whether you’re willing to devote the time and energy to setting it up and actually utilizing it.
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.
