Spot AI and Trigo both apply computer vision to retail problems, but they were built for different jobs. Spot AI is a multi-industry Video AI platform that layers AI Agents onto any existing IP camera to deliver loss prevention, operational intelligence, safety compliance, and security deterrence from a single cloud-native dashboard. The platform serves more than 1,000 customers across 17 industries with sub-one-week deployments and a flat-fee subscription that bundles hardware warranty, AI analytics, and camera health monitoring (Spot AI press release, October 2024).
Trigo is a retail-focused computer vision company founded in 2018 that specializes in autonomous checkout (EasyOut), self-checkout loss prevention, and retail intelligence for grocery and supermarket chains. The platform processes over 60 million shopping activities annually using dense ceiling-camera arrays and shelf sensors, with a stated 100% non-biometric privacy-by-design approach, four global offices, 24/7 support, and availability through Microsoft's Azure Marketplace (Trigo homepage).
The fundamental difference: Spot AI is a camera-agnostic platform covering loss prevention, operations, and safety across retail, manufacturing, and construction, while Trigo is a grocery-retail-specific system built around autonomous checkout and self-checkout shrink. This reference walks procurement teams through how that distinction shows up in deployment, operations, safety, LP, economics, and proof.
Key takeaways
- Spot AI is camera-agnostic and deploys in under one week, while Trigo specializes in grocery retail and requires purpose-installed dense ceiling-camera arrays and shelf sensors (Trigo homepage).
- Spot AI publishes named outcomes across retail, manufacturing, and multi-site commercial environments, including Storage Asset Management's elimination of break-ins across roughly 50 unstaffed facilities and Don Franklin Auto's recovery of more than $650,000 in stolen assets within one hour.
- Trigo offers genuine depth in autonomous checkout (EasyOut) and item-level SKU tracking, processing over 60 million shopping activities annually with a 100% non-biometric privacy model (Trigo homepage).
- Spot AI extends beyond loss prevention into operational intelligence, safety, and PPE compliance across manufacturing, construction, and logistics.
- Camera-agnostic deployment removes the capital cost of ripping and replacing existing ONVIF IP cameras, a structural cost advantage to model against vendors requiring proprietary hardware.
How do Spot AI and Trigo compare on camera deployment?
Spot AI connects to nearly any existing IP camera supporting RTSP, regardless of manufacturer, and deploys in under one week. Bridge33 Capital, a commercial real estate firm managing more than 25 assets across the U.S., self-installed Spot AI at each property in minutes and unified cameras from different legacy systems under a single dashboard without replacing hardware (Spot AI customer story, Bridge33 Capital). The camera-agnostic model lets retailers and multi-site operators add AI analytics to cameras already mounted on sales floors, loading docks, and parking lots without a retrofit.
Trigo's autonomous-checkout and loss prevention capabilities require a purpose-installed dense ceiling-camera array plus shelf sensors designed for item-level product tracking (Trigo technology page). That architecture delivers high-fidelity SKU recognition but involves a heavier physical installation footprint per store. Procurement teams should evaluate how each deployment model maps to their existing camera inventory, store count, and rollout timeline.
Dimension |
Spot AI |
Trigo |
|---|---|---|
Camera compatibility |
Works with any ONVIF/RTSP IP camera regardless of make or model |
Requires purpose-installed dense ceiling-camera arrays and shelf sensors |
Typical deployment time |
Under one week per site |
Requires physical installation of new camera infrastructure per store |
Existing camera reuse |
Full reuse - no rip-and-replace required |
Existing retail cameras are generally supplemented or replaced by proprietary arrays |
Multi-site scalability |
Single cloud dashboard across unlimited sites and industries |
Designed for permanent retail store environments |
How do Spot AI and Trigo compare on operational intelligence?
Spot AI's Video AI Agents deliver operational analytics that extend well beyond security: heatmaps, people counting, staffing optimization, SOP adherence, automated shift scorecards, and camera health monitoring. Don Franklin Auto, a 30-location dealership group, used AI-powered dashboards to identify why some service centers completed 30 oil changes per day while others managed only 20, generating an additional $5,000 to $10,000 in weekly income per site through operational improvements (Spot AI customer story, Don Franklin Auto). LP and operations leaders get one view of the whole facility, not just the checkout lane.
Trigo markets retail intelligence as part of its autonomous-store suite, including inventory management and shopper analytics oriented toward in-store grocery operations such as planogram compliance and stock-level monitoring (Trigo homepage). For organizations that also need to monitor receiving docks, back-of-house workflows, or non-retail facilities, Spot AI's broader operational scope covers those zones from the same platform.
Camera-agnostic platforms like Spot AI let multi-site operators unify cameras from different legacy systems under a single dashboard, eliminating the need for costly rip-and-replace projects. This structural advantage compounds as store count grows, since each new site can go live in under a week using existing IP cameras rather than waiting for proprietary hardware installation.
How do Spot AI and Trigo compare on safety and PPE?
Spot AI's pre-trained Video AI Agents detect missing PPE, forklift near-misses, crowding in hazard zones, and slip-and-fall risks in real time. In manufacturing, Spot AI customers report a 40% reduction in injuries by proactively identifying risks and improving safety procedures (Spot AI press release, October 2024). Silver Bay Seafoods, a seafood processor operating 22 locations across Alaska, achieved a 10 to 15% improvement in PPE compliance and a 15% increase in operational efficiency after deploying Spot AI's AI Agents across 10 facilities (Spot AI customer story, Silver Bay Seafoods).
Trigo's product suite is built around retail grocery checkout and in-store operations, and its public website does not market safety compliance, PPE detection, or workplace hazard monitoring. For holding companies or conglomerates that span retail and manufacturing or construction, Spot AI is the only platform in this comparison that covers safety, operations, and security across all three verticals from a single dashboard.
Dimension |
Spot AI |
Trigo |
|---|---|---|
PPE detection |
Pre-trained AI Agents detect missing hard hats, vests, and other PPE in real time |
Not a marketed capability |
Near-miss detection |
Forklift-pedestrian near-miss alerts with automated case creation |
Not applicable - retail-only product scope |
Industry coverage |
Retail, manufacturing, construction, logistics, and 13+ additional verticals |
Grocery and supermarket retail |
Safety outcome evidence |
40% injury reduction reported across manufacturing customers; 10 to 15% PPE compliance improvement at Silver Bay Seafoods |
No published safety outcome metrics |
How do Spot AI and Trigo approach retail loss prevention?
Both platforms address retail shrink, but from different angles. Trigo specializes in self-checkout loss prevention through a virtual shopping list that compares scanned items against observed items in real time at SCO stations, and its EasyOut autonomous checkout enables grab-and-go shopping without customer registration (Trigo homepage). For grocery chains pursuing checkout-free experiences or granular SKU-level tracking, Trigo's depth here is a meaningful differentiator. The platform displays logos of global retail leaders including ALDI Nord and states it processes over 60 million shopping activities annually.
Spot AI addresses shrink across every store zone - POS exceptions, perimeter intrusions, parking-lot license plate recognition, and in-aisle activity - using cameras already in place. Storage Asset Management, which operates approximately 50 unstaffed facilities, eliminated break-ins at one location after Spot AI detected intruders at 1 AM and alerted police who arrived during the crime (Spot AI customer story, Storage Asset Management). The built-in Cases tool lets LP teams manage investigations end to end, and AI-powered search reduces investigation time from hours to minutes. For LP directors managing shrink across receiving docks, sales floors, parking lots, and POS, Spot AI covers the full footprint without a dense ceiling-array retrofit.
Dimension |
Spot AI |
Trigo |
|---|---|---|
LP coverage scope |
Full-store: POS, perimeter, parking lot LPR, in-aisle, back-of-house |
Primarily self-checkout lanes and in-store autonomous checkout zones |
Item-level SKU tracking |
Not a claimed capability |
Real-time individual SKU identification as shoppers pick and place items |
Investigation tools |
AI-powered search, Cases tool, single-click video sharing, LPR alerts |
Real-time SCO discrepancy alerts; broader investigation tooling not detailed publicly |
Autonomous checkout |
Not pursued - focuses on LP and operations across existing checkout infrastructure |
EasyOut grab-and-go checkout without customer registration |
Privacy model |
Role-based access controls, SSO, secure-by-design architecture |
100% non-biometric data processing, privacy-by-design (Trigo homepage) |
How do Spot AI and Trigo compare on deployment costs?
Neither vendor publishes a complete public pricing catalog, so this section focuses on the structural cost drivers buyers should evaluate during procurement. Trigo's SCO loss prevention module is listed on Microsoft's Azure Marketplace starting at $100 per SCO per month with a $500 per store per month minimum, covering only self-checkout loss prevention; full autonomous-store deployments carry additional hardware and integration costs not detailed in that listing. Spot AI's subscription bundles the NVR appliance with hardware warranty, AI analytics, camera health monitoring, and open API access at a per-camera tier - with no per-SCO metering or separate hardware purchase required.
The most significant cost variable is camera reuse. Spot AI's camera-agnostic model lets retailers keep existing IP cameras in place, avoiding the capital expenditure and installation labor of a full ceiling-array retrofit. Procurement teams evaluating both vendors should request itemized quotes that separate software subscription, hardware costs, installation labor, per-unit metering, and ongoing maintenance, then model total cost across a three-to-five-year horizon that accounts for camera refresh cycles and multi-site rollout timelines.
Dimension |
Spot AI |
Trigo |
|---|---|---|
Deployment model |
Camera-agnostic - connects to existing IP cameras via plug-and-play NVR |
Proprietary dense ceiling-camera arrays and shelf sensors installed per store |
Camera reuse |
Full reuse of existing ONVIF/RTSP cameras |
Existing cameras generally supplemented by new proprietary hardware |
Typical deployment time |
Under one week per site |
Physical installation project per store (timeline not publicly specified) |
Hardware refresh |
Existing cameras continue in service; NVR appliance included in subscription |
Proprietary camera arrays and sensors subject to vendor refresh cycle |
Pricing transparency |
Per-camera subscription bundling NVR, AI, warranty, and camera health monitoring |
SCO module from $100/SCO/month ($500/store minimum) on Azure Marketplace; autonomous-store pricing not publicly listed |
When is Trigo a better fit than Spot AI?
Trigo is purpose-built for retail grocery operations and covers multiple use cases within that vertical, including loss prevention, autonomous checkout, and retail intelligence (Trigo homepage). For a large supermarket chain whose primary objective is deploying checkout-free shopping experiences or achieving item-level SKU tracking for planogram compliance, Trigo's specialized depth is a genuine advantage. The platform's 100% non-biometric privacy model and availability through Microsoft's Azure Marketplace may also simplify procurement for enterprise IT teams already invested in the Azure ecosystem.
Trigo demonstrates production scale - processing over 60 million shopping activities annually - and has earned industry recognition including Forbes AI50 (2023) and RETA Awards 2026 Top Supplier Retail Winner. Buyers whose requirements are confined to grocery autonomous checkout and SCO shrink detection, with no need for manufacturing safety, construction site security, or multi-industry dashboard consolidation, should evaluate Trigo's specialized capabilities alongside Spot AI's broader platform scope to determine which architecture better matches their operational footprint.
When evaluating total cost of ownership, request itemized quotes from both vendors that separate software subscription, hardware costs, installation labor, per-unit metering, and ongoing maintenance. Model total cost across a three-to-five-year horizon that accounts for camera refresh cycles, multi-site rollout timelines, and whether your existing IP cameras can be reused or must be supplemented with proprietary hardware.
What proof points support Spot AI and Trigo?
Spot AI publishes named customer outcomes across multiple verticals relevant to this comparison. Storage Asset Management (approximately 50 unstaffed storage facilities) eliminated break-ins at one location after real-time AI detection and police coordination, and now manages all sites remotely with enhanced confidence in security (Spot AI customer story, Storage Asset Management). Don Franklin Auto (30 dealership locations) recovered five of six stolen vehicles worth $130,000 each within one hour, saved 10 to 15 hours per week in HR video review time, and generated an additional $5,000 to $10,000 in weekly service center income per site (Spot AI customer story, Don Franklin Auto). In manufacturing, Silver Bay Seafoods achieved a 15% increase in operational efficiency and 10 to 15% improvement in PPE compliance across 10 facilities in Alaska (Spot AI customer story, Silver Bay Seafoods).
Trigo displays logos of global retail leaders on its homepage, including ALDI Nord, and references a partnership with Vista Technology Support to expand real-time loss prevention in the UK and Ireland (Trigo homepage). Comparable named-customer outcome metrics - shrink reduction percentages, investigation time improvements, or ROI figures - were not located on Trigo's public site. Procurement teams should request case studies with quantified outcomes from both vendors during the evaluation process.
Reference summary
Spot AI and Trigo serve overlapping but structurally different buyer needs. Trigo offers specialized depth in grocery autonomous checkout and self-checkout loss prevention, backed by item-level SKU tracking and a non-biometric privacy architecture. Spot AI offers broader platform scope - covering retail loss prevention, operational intelligence, safety compliance, and security deterrence across retail, manufacturing, construction, and logistics - with camera-agnostic deployment that reuses existing IP cameras and goes live in under one week.
Spot AI publishes named customer outcomes across multiple verticals; comparable public outcome metrics from Trigo were not identified during this review. Procurement teams evaluating both platforms should weight their requirements across industry breadth, camera infrastructure compatibility, deployment timeline, and the specific LP use cases (checkout-only vs. whole-store) that drive their shrink-reduction mandate.
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Frequently asked questions
What does PCI DSS 4.0 require when security cameras can capture payment card data at self-checkout or cashier lanes?
PCI DSS 4.0 requires organizations to protect account data wherever it appears, including in camera views or exported clips that may capture primary account numbers (PCI SSC). Buyers should ask whether each vendor's deployment architecture reduces card-data exposure by design, through camera placement, masking, and retention controls.
How does Trigo's non-biometric privacy model affect procurement compared to platforms that process standard video feeds?
Trigo states it uses 100% non-biometric data processing with a privacy-by-design approach, which may simplify compliance in jurisdictions with strict biometric data laws (Trigo homepage). Procurement teams should request documentation of how each vendor classifies and processes personal data and verify compliance with GDPR, BIPA, or CCPA based on their operating jurisdictions.
Can a retailer deploy Trigo's autonomous checkout alongside a separate whole-store video AI platform like Spot AI?
Architecturally, Trigo's dense ceiling arrays serve checkout and in-aisle zones while a camera-agnostic platform like Spot AI can layer onto existing cameras covering perimeter, parking lot, back-of-house, and POS. Buyers should evaluate integration complexity, overlapping coverage, and whether one platform can meet enough use cases to avoid managing two systems.
How should retailers evaluate edge versus cloud video architecture for computer-vision stores with many cameras?
NIST guidance on IoT cybersecurity recommends understanding device data flows, external dependencies, and the security implications of cloud-mediated control before deployment decisions are made (NIST IR 8259). Model camera count, frame rate, retention, WAN redundancy, and outage tolerance to compare edge-heavy designs that preserve local operation against cloud-heavy designs that simplify centralized updates.
What should buyers require for video retention, evidence integrity, and chain of custody if store video may be used in investigations or litigation?
The U.S. Department of Justice's digital evidence guidance emphasizes preserving integrity, documenting handling, and maintaining a clear chain of custody so evidence remains reliable for legal proceedings (NIJ). Ask whether exported clips are hashed, whether metadata is preserved, and how long originals remain available under legal hold.
About the author
Sud Bhatija is COO and Co-founder at Spot AI, where he scales operations and GTM strategy to deliver video AI that helps operations, safety, and security teams boost productivity and reduce incidents across industries.
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