The best AI video analytics companies in 2026, sorted by what they do with a camera feed
Spot AI builds video AI agents that act on what a business's existing cameras see, and that is only one of four things sold as AI video analytics. The other companies here route detections to people, sell toolkits to engineers, or add analytics to a video management system (VMS), and that difference decides who handles an incident at 2 a.m. Nearly 68% of retail executives in Deloitte's 2026 outlook survey expect to deploy agentic AI for key operational and enterprise activities within 12 to 24 months (Source: Deloitte), so the word "agent" no longer sorts vendors. This guide sorts 12 companies by what each documents on its own site as of October 2026 and says where Spot AI fits and where it does not.
Key takeaways
- AI video analytics companies sell four products in 2026: agents that act, detection and triage tools, developer toolkits, and analytics added to a VMS.
- Spot AI sits in the first group: its agents run on the ONVIF IP cameras a business already owns and respond with strobes, horns, and natural-conversation talkdown.
- Acting or alerting separates the companies more than any feature, because an alert moves only as fast as the person who reads it.
- "Works with your cameras" needs a follow-up: which analytics still run on third-party cameras.
- Spot AI fits multi-site operators with cameras already installed and incidents that happen when nobody is watching.
Key terms
- Video AI agent: a detection that carries its own next step, such as a talkdown or a message to a named person. Spot AI ships more than 15 pre-trained agents.
- Intelligent Video Recorder (IVR): Spot AI's on-site recorder, which connects ONVIF IP and analog cameras and keeps full-resolution video in the building.
What does an AI video analytics company actually sell?
Spot AI sells agents that act on a camera feed, while the other companies here sell detection and triage, toolkits, or analytics layered onto a VMS. All four read the same video and differ in how much of the incident they hand back to your team:
- Agents that act. The system takes a first action on site, such as a spoken warning, strobes, or a door lockdown, before anyone reviews the event.
- Detection, triage, and investigation. The product finds and sorts events, then routes most of them to a person.
- Developer toolkits. Models, SDKs, and pipelines that engineers or camera makers turn into a product.
- Analytics added to a VMS. A recording platform first, with detection added through modules or partners.
The split matters because losses arrive as patterns. In NRF's 2026 theft and violence survey, 50% of retailers reported higher rates of repeat offenders, 40% more ORC-related incidents, and 37% more walkout or pushout theft (Source: National Retail Federation). A repeat offender shows up only to a system that links the same plate, clothing, or route across visits. The explainer on how video intelligence software works covers the technology, and the decision guide to business security camera systems the hardware.
The 12 companies at a glance:
Company | What it does with the feed | Best for |
|---|---|---|
Spot AI | Spot AI's agents detect behavior, deter on site, and keep case-ready evidence | Multi-site operators that need incidents handled after hours without adding people |
Verkada | Plays escalating, partly AI-written audio warnings through Verkada speakers | Organizations standardizing on Verkada hardware |
Lumana | Its Response agent notifies staff, broadcasts audio, and triggers lockdowns | Retailers that want POS correlation on existing cameras |
Coram | Agents reconstruct an incident across cameras and doors into a report | Teams whose heaviest work is investigation |
Ambient.ai | Confirms or clears access control alarms with video | Security operations centers with heavy alarm volume |
Solink | Pairs video with POS and other business data to flag exceptions for review | Restaurant and retail chains whose loss work starts at the register |
Irisity | Runs open analytics from the camera edge to the cloud | Integrators with mixed camera estates |
PureTech Systems | Geo-locates and tracks targets along long perimeters | Borders, airports, seaports, and utilities |
NVIDIA Metropolis | Supplies SDKs, models, and blueprints for visual AI agents | Engineering teams building a product |
IntelliVision | Embeds analytics in OEM cameras | Camera makers and large integrators |
Milestone XProtect | Records on an open VMS, with analytics through BriefCam | Organizations keeping a Milestone estate |
Eagle Eye Networks | Records in a cloud VMS, with AI search and alerts | Teams moving recording to the cloud |
Ask every vendor on the shortlist the same question on the first call: what does the product do, by itself, in the ten seconds after it detects someone? The answer places the company in its category faster than any feature sheet.
Which AI video analytics companies act on what they see?
Spot AI, Verkada, and Lumana are the three companies here that put an automatic on-site response to everyday incidents at the center of the product, such as audio that plays before anyone reviews the event. They differ in what the response is, which hardware it needs, and how much of the case they finish afterward.
Spot AI
Spot AI runs video AI agents on the ONVIF IP cameras a business already owns, including Avigilon, Axis, Hanwha, and Pelco models, and reaches legacy analog cameras through its IVR. Its retail workflow is detect, deter, investigate, and resolve: agents read behavior in context, trigger strobes, horns, or escalating natural-conversation talkdown, notify a named person, auto-resolve routine incidents, and organize timestamped clips into cases. Spot AI keeps full-resolution video on site and sends only metadata across the network, which keeps deployments PCI-clean. Spot AI follows NDAA-compliant and SOC 2 practices, serves more than 1,100 US customers, and most sites go live in days.
What to verify in a demo: a week of detections from your highest-loss site, and how many your team dismisses.
Verkada
Verkada's AI-Powered Deterrence plays up to three escalating messages before raising an alarm: the customer writes the first, and AI writes the next two from context, which can include what the person is wearing. Deterrence supports third-party cameras, and the messages play on Verkada audio: the BZ11 horn speaker, Verkada Intercom models, and Verkada Sound Systems. Non-Verkada cameras join through Command Connector, which offers basic analytics such as people and vehicle search; license plate of interest alerts are not supported there, and loitering and line crossing may not be available on every channel.
What to verify: which Verkada speakers each site would need for deterrence.
Lumana
Lumana describes itself as an enterprise video security system with AI agents, built on its own VIA-1 model, which it calls camera agnostic. Its Response agent can notify staff, broadcast audio, trigger lockdowns, and push actions to other systems through API or GPIO, with human verification before emergency dispatch. For retail, Lumana correlates POS data with video to flag voids, no-sales, and sweethearting. Its trust page states SOC 2 Type 2 and NDAA compliance.
What to verify: whether the audio is a preset message or one that reacts to the person and escalates.
Which companies lead with detection, triage, and investigation?
Spot AI acts on site, while Coram, Ambient.ai, Solink, Irisity, and PureTech Systems lead with detection and route most events to people, each with a specialty: investigation, alarm triage, transaction exceptions, open analytics, and long perimeters. Some automate part of the response, such as Coram's emergency lockdowns.
Coram
Coram describes itself as an AI-native platform that unifies video, access, and response, and says it works with any IP camera. Its distinctive feature is Deep Investigation: autonomous agents reconstruct what happened across cameras, doors, and time periods and return a synthesized timeline and a shareable report. Its automated actions center on emergencies, with weapon detection tied to mass notifications and lockdowns. Coram states SOC 2 Type II and HIPAA audits.
What to verify: what the system does during the incident, not only afterward.
Ambient.ai
Ambient.ai calls its approach agentic physical security and runs Ambient Pulsar, a reasoning vision-language model built for physical security, with more than 150 verified threat signatures. Its core job is alarm triage: correlating video with access control (PACS) data to confirm or clear alarms. It works with any RTSP-enabled camera and displays a SOC 2 Type II badge.
Solink
Solink describes its platform as AI vision intelligence that brings video, data, and operations together, and says it runs on existing cameras. Its exception-based reporting pairs video with POS, labor, inventory, and access control data through more than 375 integrations, so investigators review a short list of flagged refunds, voids, and loyalty abuse, each with the matching clip. Its AI Video Alarms let AI filter intrusion events and people verify them, with optional alarm hardware for strobes and talk-down. Solink's security page states SOC 2 Type 2 and NDAA compliance.
What to verify: which agent actions run today, since Solink's AI Agents FAQ lists deterrent and gate-lock triggers as coming soon.
Irisity
Irisity, which acquired Agent Vi, sells IRIS+, an open AI video analytics platform that it says works with any camera brand. It deploys on premises, hybrid, in the cloud, or on the camera edge, with detection agents for intrusion, loitering, smoke and fire, unattended objects, and line crossing.
PureTech Systems
PureTech Systems builds perimeter security automation for critical infrastructure and borders. Its PureActiv software geo-locates detected objects, locks PTZ and fixed cameras on to a target, and detects at ranges up to 5 miles at sites such as airports, seaports, and utilities. PureTech says PureActiv also delivers proactive deterrence.
Which companies sell a developer toolkit instead of a finished product?
Spot AI sells a finished system, while NVIDIA Metropolis and IntelliVision sell building blocks that another company turns into a product. Both fit an engineering team or a camera maker, not a security team that needs coverage next quarter.
NVIDIA Metropolis
NVIDIA describes Metropolis as a vision AI application platform and partner ecosystem for building visual AI agents from the edge to the cloud. The kit includes the DeepStream SDK, TAO for customizing models, and a blueprint for video search and summarization, and the ecosystem counts more than 1,000 companies. Spot AI's own edge AI runs on NVIDIA GPUs.
What to verify: who owns accuracy, alert workflow, and support after the prototype.
IntelliVision
IntelliVision sells embedded smart camera analytics software designed for OEMs and large integrators, covering motion, human and vehicle detection, audio analytics, and license plate recognition, plus edge-based vision language AI for ATM security.
Which VMS platforms add AI analytics on top of recording?
Spot AI records video and runs its agents in one system through the IVR, while Milestone and Eagle Eye Networks are recording platforms first, with detection added on top. Both fit an organization keeping its VMS, a decision the 2026 video management software comparison covers vendor by vendor.
Milestone XProtect
Milestone describes XProtect as an open-platform VMS with the market's widest choice of cameras, sensors, and IoT devices, integrating with over 1,000 third-party applications. It runs on Husky appliances, on AWS, or at remote sites with Arcules, and advanced analytics such as Video Synopsis come through BriefCam.
Eagle Eye Networks
Eagle Eye Networks runs a cloud VMS that works with more than 7,500 cameras and extracts AI-driven analytics from virtually any ONVIF-conformant camera. Documented features include natural-language search, gun detection, license plate recognition, video of suspicious purchases or returns, and talk-down alerts. Eagle Eye stores video encrypted in its own data centers and has merged with Brivo.
How do the four categories compare on six buying criteria?
Spot AI's column differs most on deterrence and evidence, the two criteria that decide what happens after a detection. The other columns summarize what the companies above document:
Criterion | Spot AI | Other agents that act | Detection and triage | Developer toolkits | VMS add-ons |
|---|---|---|---|---|---|
Detection | Spot AI runs 15+ pre-trained agents, plus custom detections built in natural language with Iris | Pre-built; fewer analytics on third-party cameras at Verkada | Investigation, alarm triage, transaction exceptions, perimeter tracking | Whatever your team trains | Basics, with advanced analytics as add-ons |
Deterrence | Spot AI triggers strobes, horns, and escalating talkdown without waiting for a person | AI-written messages at Verkada, broadcast audio at Lumana | Mostly routed to a person; emergency lockdowns at Coram | Built by your team | Optional, such as Eagle Eye's talk-down alerts |
Evidence | Spot AI auto-resolves routine incidents and keeps case-ready evidence for the rest | Footage search; an Investigate agent at Lumana | A shareable report from Coram's agents | Built by your team | Retention, search, and clip sharing |
Deployment on existing cameras | Spot AI connects any ONVIF IP camera and reaches analog units through the IVR | Camera agnostic at Lumana; a compatibility list at Verkada | Any IP or RTSP camera at Coram and Ambient.ai | Your own pipeline | Broad, such as 7,500+ cameras at Eagle Eye |
Integrations | Spot AI offers open APIs, webhooks, a read-only MCP endpoint, POS, and access control | POS, API, and GPIO actions at Lumana | Deep in one area, such as access control alarms or POS data | Anything you build | Over 1,000 applications at Milestone |
Data security | Spot AI keeps full-resolution video on site and is NDAA-compliant, SOC 2, and PCI-clean | SOC 2 Type 2 and NDAA at Lumana | SOC 2 Type II at Coram and Ambient.ai | Your own controls | Eagle Eye's data centers; Husky or AWS at Milestone |
See where your own sites land on this matrix. Spot AI runs its agents on footage from your cameras and shows each step from detection to closed case. Book a demo on your own footage, and use the 60-day video AI pilot plan to decide what that demo has to prove.
How do you test a shortlist before you sign?
Spot AI's advice is to test every finalist on your own footage and to time the whole incident, not the alert, which is why its own evaluations start from a customer's existing video. Four checks:
- Bring your hardest footage. A night of lot video and a busy register hour, not the vendor's reel.
- Count dismissals, not detections. Route a week of detections to a queue and count what your team throws away.
- Time the whole incident, from detection to first action to a closed case. Evidence is where programs leak: 63% of retailers in NRF's survey report fewer than half of their store theft incidents to law enforcement, citing low-dollar losses or not meeting felony thresholds (60%) and concerns about law enforcement response and follow-through (54%) (Source: National Retail Federation). Low-dollar incidents reach a felony threshold only when someone links them.
- Check the cameras and data rules you keep. Ask which analytics run on third-party cameras, as the guide to adding AI to an existing camera network explains, and take the SOC 2 checklist for video platforms to IT before the pilot.
Write the pilot's success criteria before it starts: dismissals per week, minutes from detection to a closed case, and the share of incidents that reach law enforcement. A vendor that agrees to those three numbers in writing knows which category it is in.
Is Spot AI the right fit for your sites?
Spot AI fits operators who run many sites on cameras they already own and need incidents handled in the moment, not flagged for later. Four signs it fits:
- More sites than the team can visit. A lean security or loss prevention team covers dozens of locations.
- Cameras already on the walls. ONVIF IP cameras, legacy analog units, or both, with no plan to replace them.
- Incidents when nobody is watching. After-hours activity in lots, forecourts, loading docks, and perimeters.
- A number to move. Shrink, incidents per site, or hours per investigation, with a month of baseline and one owner who can approve a proof of value.
Another category is the better buy when engineers want to build (a toolkit), when the work is access control alarms in a staffed operations center (a triage specialist), when the recording platform stays and basic detection is enough (its add-ons), or when the fence line runs for miles (a perimeter specialist).
A Spot AI evaluation usually runs in five steps:
- A demo on video from your own cameras.
- A technical check with IT on where video is stored, the choice the guide to cloud-only, hybrid, and on-premises camera architecture lays out.
- A business case built on your baseline.
- A proof of value on a few representative sites.
- A rollout plan with the site template and alert routing a multi-site camera operating model needs.
Unique Industries, America's largest manufacturer and distributor of party supplies, shows lean-team coverage at work. It runs Spot AI's video AI agents across a 1-million-square-foot distribution facility in Virginia, where a safety team of three also covers a 400,000-square-foot building and more than 450 employees on three shifts. The company reports investigation time cut from hours to minutes, and its asset protection lead puts the posture this way:
"With Spot AI, we're not Big Brother, and we're not here to spy on anyone. We're here to keep people and property safe, and make sure no one comes in to cause harm."
Kevin McDaniel, Director of Safety and Asset Protection, Unique Industries
Spot AI is the company to call first when the problem is the incident itself, not the recording or the investigation afterward. Book a demo with a week of footage from your hardest site, or read the Spot AI customer stories first.
Frequently asked questions
What is AI video analytics?
Spot AI defines AI video analytics as software that reads camera feeds the way a trained person would, recording people, vehicles, objects, and behavior as searchable events instead of hours of footage. Earlier analytics fired on motion, which is why a swaying branch could trigger an alarm. Current systems use vision-language models that weigh context, such as the hour, the zone, and what a person is doing.
Can AI video analytics run on the cameras we already have?
Spot AI runs on any ONVIF IP camera and connects older analog cameras through its IVR, so most estates start with the cameras already installed. Placement is the other half of the answer: walk one site with the vendor and mark which camera each detection would use, because a camera facing glare supports far fewer detections than one with a clear view.
What is the difference between a VMS and a video AI platform?
Spot AI's short answer: a VMS stores and retrieves video, while a video AI platform decides what the video means and acts on it. To tell which one a vendor sells, ask what happens if nobody opens the software for a week. A VMS keeps recording; a video AI platform keeps deterring, notifying, and building cases.
How does AI video analytics help reduce retail shrink?
Spot AI helps reduce the likelihood of loss by catching patterns a store team cannot watch for all day, such as a plate of interest returning to the lot or someone lingering by the stockroom door after close. Detection alone changes little. The gain comes from a response while the person is still on site, such as a talkdown or a message to the manager on duty.
What data security questions should we ask an AI video analytics company?
Spot AI answers the first question most IT teams ask, where the video lives, with its IVR: full-resolution video stays in the building and only metadata crosses the network. Then ask every vendor who can view footage and how access is logged, whether its SOC 2 report is Type II and current, whether its hardware is NDAA-compliant, and whether cameras stay off the POS network. Spot AI does not use biometric identification.
About the author
Dunchadhn Lyons, Director of AI Engineering. Dunchadhn Lyons leads Spot AI's AI Engineering team, building real-time video AI for operations, safety, and security, turning video data into alerts, insights, and workflows that cut incidents and boost productivity.