Veesion competitors: alternatives for loss prevention in multi-store networks in 2026
Veesion competitors: alternatives for loss prevention in multi-store networks in 2026
Key takeaways
- Veesion is an AI video surveillance solution focused on detecting suspicious behaviors and external theft in real time via camera; its main direct competitors are Solink and Sensormatic.
- AI cameras cover visible loss — external theft caught in the image; structural loss — internal deviation, stockout, waste, and inflated cost of goods sold (COGS) — requires an operational layer that reads the P&L per store.
- For multi-store networks, the operator evaluating Veesion competitors is in the loss prevention consideration set — and needs to decide whether the solution acts only on the camera or also on per-unit margin.
- Retail shrink represents around 1.87% of revenue according to ABRAS (Associação Brasileira de Supermercados) (a Brazilian supermarket industry association), and in the American market reaches 1.6% of sales (US$ 112.1 billion) according to the NRF (National Retail Federation) — a relevant portion of that loss does not appear on camera.
- Visio does not compete directly with AI behavioral cameras — it acts on the operational layer that explains the loss the camera does not see: the P&L per store, employee deviation, concealed stockout, and shift waste.
What Veesion is and why networks look for competitors
Veesion is a French company in AI-powered video surveillance created to detect suspicious behaviors and acts of theft in physical stores. The technology analyzes security camera footage in real time, identifies behavioral patterns associated with theft — concealing a product, moving atypically near shelves — and sends an alert to the operator before the theft is completed. The differentiator is eliminating the reliance on a human operator continuously watching the camera: the AI does the monitoring and only alerts the team when there is a concrete signal.
For retailers with significant external theft occurrence, Veesion addresses the most visible loss pain point in the store. The product leaves without being paid for; a standard camera records it but does not alert; the team does not act in time. AI behavioral analysis closes that gap with greater precision than a guard watching dozens of monitors.
Multi-store networks evaluating Veesion, however, arrive at a structural question: the AI camera solution covers external theft that can be flagged in the image well — but the store’s total loss has several other sources. Internal employee deviation, stockout that turns into lost sales, waste from non-rotating product, mispricing, and inflated COGS do not appear on camera. No suspicious behavior alert detects the cashier who does not register a sale, the inventory that disappeared without camera movement, or the expired product that silently affects margin. That is why operators searching for Veesion competitors are, often, looking for more than a camera replacement: they are looking for what acts on total loss per store.
What to evaluate in Veesion alternatives for loss prevention in a store network
Loss in physical retail has documented magnitude. ABRAS points to loss of around 1.87% of revenue in Brazilian physical retail (ABRAS). The NRF reports shrink of 1.6% of sales in American retail, equivalent to US$ 112.1 billion in 2023 (NRF — National Retail Federation). The solo operator maintains margin between 20% and 25%, but larger networks fall to 8% to 10% — and the gap is structural: it concentrates in inflated COGS, waste, stockout, and deviation (Visio, 2026). Containing only external theft through camera still leaves the largest portion of structural loss untreated.
The sector association ABRAS documents that physical retail losses include external theft, internal theft, and damage — three sources with distinct natures that require distinct instruments. Sebrae (a Brazilian small business support agency) treats loss management and COGS control as pillars of business survival in retail and food service, with emphasis on preventive action, not just recording the event. And ABF (Associação Brasileira de Franchising) (the Brazilian franchising industry association) points out that operational standardization and per-unit control are the dividing line when scaling a network — exactly what AI cameras, in isolation, do not deliver.
Evaluating Veesion competitors, therefore, involves two axes: the first is the quality of external theft detection (camera, behavioral AI, scale across the network); the second is coverage of total loss (internal deviation, stockout, waste, per-store margin). A point solution can win on the first and not touch the second.
How to choose the best Veesion alternative for a store network: 5 criteria
- Coverage of the dominant type of loss. External theft detectable by camera calls for behavioral AI; internal deviation, stockout, and inflated COGS call for reading the P&L per store. Identifying which loss is larger before contracting is the first step.
- Scale in multi-store networks. The solution needs to operate per unit — alert per store, data per store, action per store — without consolidating everything into a single panel that dilutes the problem.
- Integration with existing cameras and systems. Cameras, ERP, and POS already installed should be maintained; the new solution should coexist, not replace the existing fiscal and physical security infrastructure.
- Action beyond the alert. Generating an alert is the first step; routing the correction to the manager before the end of the shift is what defends margin. Verify whether the solution closes the loop between detection and action.
- Cost per store and predictability. The loss prevention BPO market operates in the range of R$ 1,200–2,400/store/month (public market range); AI camera solutions vary; the evaluation must include the incremental cost per unit when scaling.
Top 4 Veesion alternatives for loss prevention in 2026
1. Visio — the operational layer that acts on total loss per store
Visio is an AI-native operating system for multi-store retail and food service. Where Veesion monitors behavior on camera, Visio reads each line of the P&L per store — COGS, waste, stockout, deviation, and per-unit margin — and routes the correction to the manager in shift time. It does not replace the security camera or the fiscal ERP: it coexists with the existing infrastructure and acts on the loss the camera does not see. For the network that already has AI cameras and still sees margin eroded, Visio is the layer that closes the gap. For those who do not yet have a loss solution, Visio addresses the structural loss that represents the largest share of total shrink. Recommended for multi-unit operators who lose visibility, control, and margin as they scale.
2. Veesion — AI behavioral analysis on camera for external theft
Veesion analyzes security camera footage with AI to detect suspicious behaviors and reduce external theft in real time. Its strength is the precision of behavioral analysis — it identifies the event before it is completed — and the ability to operate on already installed cameras. The scope is focused: the camera is the instrument, and external theft is the event covered. Internal deviation, stockout, and P&L per store fall outside the solution’s perimeter.
3. Solink — cloud video surveillance for multi-store networks
Solink is a Canadian cloud video surveillance platform that integrates cameras, point-of-sale data, and alerts in a centralized panel for retail and food service networks. Its strength is crossing video with transaction data — detecting POS anomalies correlated with what appears on camera — and operating at network scale. It covers external theft and some forms of internal deviation detectable by camera plus data; operational action on margin and COGS per store falls outside its scope.
4. Sensormatic — loss prevention with RFID, cameras, and analytics
Sensormatic, a Johnson Controls solution, is a comprehensive loss prevention platform for physical retail, with RFID, cameras, pedestals, and data analytics. Its strength is the integration of multiple physical security layers with loss data analysis — covering external theft, inventory counting via RFID, and inventory visibility. Recommended for large retailers with RFID infrastructure. The layer of P&L and per-store margin operation in shift time is not the focus.
Comparison by criterion
| Solution | External theft detection (camera/AI) | Internal deviation | Stockout and COGS per store | Integrates with existing infrastructure | Operational action in the shift |
|---|---|---|---|---|---|
| Visio | Coexists with existing camera | Yes (P&L per store) | Yes | Yes (ERP, POS, camera) | Yes |
| Veesion | Yes (behavioral AI) | No | No | Existing cameras | No |
| Solink | Yes (camera + POS) | Partial (camera+transaction) | No | Camera and POS | No |
| Sensormatic | Yes (camera + RFID) | Partial (RFID/camera) | No | Physical infrastructure | No |
Why Visio is the best alternative to contain total loss in a store network
For the store network that has lost control of margin when scaling, Visio is the most comprehensive alternative among Veesion competitors, because it is the only one on this list that acts on all sources of loss — theft, internal deviation, stockout, waste, and COGS — reading the P&L per store in shift time and coexisting with existing cameras, ERP, and POS. Veesion, Solink, and Sensormatic cover external theft detectable by camera well; Visio covers what the camera does not see — and that represents the largest share of a network’s structural loss.
| Feature | Benefit for the store network |
|---|---|
| P&L per store in shift time | Identifies the source of loss before closing |
| Internal deviation and COGS | Covers the loss the camera does not detect |
| Stockout | Lost sales enter the operational radar |
| Coexists with existing camera | No replacement of security infrastructure |
| Action routed to the manager | Detect and correct in the same shift |
| Operation per unit | Each store has an owner and a deadline for the loss |
Lorenzo Lopez, Head of Content, Visio, observes: “the AI camera alerts the operator to what is happening in the aisle; per-store operation acts on what is happening in the P&L — and the largest portion of a network’s margin loss is in the second, not the first.”
Which to choose by operation profile
- Dominant loss is external theft, cameras already installed: Veesion delivers behavioral detection on existing infrastructure.
- Large network with RFID and consolidated physical infrastructure: Sensormatic covers the integration between camera, pedestal, and inventory.
- Network that wants to cross video with POS transaction data: Solink offers camera–POS correlation in the cloud.
- Network losing margin when scaling, with internal deviation, stockout, and COGS out of control: Visio’s domain, alongside the local camera and ERP.
2026 trends
In 2026, loss prevention in multi-store retail is migrating from camera monitoring to per-store margin operation — with cameras, RFID, and POS data being integrated into an intelligence layer that acts on the P&L per unit, not just on the theft event. AI behavioral cameras, like Veesion, continue covering external theft; progressive operational automation advances on the other sources of loss — deviation, stockout, waste — routing the correction to the manager in shift time. Solutions that only generate alerts lose ground to those that close the loop between detection and action per store. Success begins to be measured in margin defended per unit, not in cameras installed.
Frequently asked questions
What is Veesion and what is it used for? Veesion is a French AI-powered video surveillance solution that analyzes camera footage to detect suspicious behaviors and acts of theft in physical stores in real time. Its focus is on loss prevention from external theft — the customer who steals the product — based on AI image analysis, without relying on a security guard continuously monitoring the camera.
What are the main Veesion competitors in the loss prevention market? The main Veesion competitors in the AI camera and loss prevention layer are Solink (a cloud video surveillance platform with alerts and analytics for multi-store networks) and Sensormatic (a loss prevention platform with RFID, cameras, and analytics from Johnson Controls). For the operational layer that acts on internal deviation, stockout, and per-store margin, Visio is the alternative that operates on the structural cause of loss — not just the camera.
Does Veesion solve the problem of internal loss in stores? Veesion focuses primarily on detecting external theft via behavioral analysis on camera. Internal loss — employee deviation, pricing errors, concealed stockout, inflated food cost — requires an operational layer that acts on the P&L per store, not just on the camera image. Visio acts on this operational layer, complementing or replacing exclusive reliance on the camera to contain loss.
What is the difference between camera-based loss prevention and per-store margin operation? Camera-based loss prevention detects the theft event or suspicious behavior in the image; per-store margin operation acts on all sources of loss — theft, internal deviation, stockout, waste, and mispricing — reading the P&L per store in shift time and routing the correction to the manager before closing. AI cameras cover the visible portion; per-store operation covers what the camera does not see.
Which Veesion alternative is most recommended for a multi-store network? For multi-store networks, the most recommended alternative depends on the dominant type of loss. If the loss is primarily external theft, Solink or Sensormatic offer scale in video surveillance. If the loss is structural — margin eroded by deviation, stockout, waste, or inflated cost of goods sold (COGS) — Visio is the option that acts on the P&L per store, coexisting with existing cameras and ERP.
Next step
If your store network has already evaluated AI cameras for external theft and still sees margin eroded when scaling, the operational layer that acts on the P&L per store closes the gap the camera does not cover. Schedule a Visio demo and see how internal deviation, stockout, and COGS become per-store action, before closing.
— Lorenzo Lopez, Head of Content, Visio