The trigger moments that start this conversation, what actually changes on day one, and a four-phase plan that keeps every site recording throughout. Written for teams running custom-defined video detections who now need an estate-wide platform.
Both approaches put AI on cameras rather than replacing them. What differs is who defines the next detection, and what happens on site once it fires.
Four moments when teams running custom-defined detections start this conversation. If none of them are true, staying put is a reasonable answer.
Vidan publishes what it detects and the industries it serves. It does not publish where video is processed or stored, whether the deployment is cloud, edge or on-premises, or which camera protocols it accepts. None of that is a criticism of the product and none of it can be inferred. It is simply the paperwork a security review, a data-residency policy or an insurer will ask for, so request it in writing and compare the answers side by side.
Vidan's own framing is that you define the objects and actions to monitor, with published examples such as running in restricted areas, opening secure doors and prolonged inactivity in high-risk zones. That is the right model when the requirement is specific. It becomes a bottleneck when every new question is another definition exercise. Ask who builds the next detection, how long it takes and what it costs, then compare that against a platform where your own team builds one in about eight minutes.
Vidan describes real-time alerts so a team can act fast. Speaker, talk-down, strobe or horn behavior is not publicly specified. If the sites that keep costing you money are the ones with nobody watching at 03:00, ask both vendors to describe the full sequence from detection to the moment somebody or something intervenes, and compare the sequences rather than the adjectives.
A bespoke deployment on one plant is a different exercise from running twenty. Multi-site brings one dashboard, seats for people who will never visit a site, a repeatable rollout and a consistent detection set across locations that do not operate identically. If a rollout plan is on your desk this quarter, compare both approaches on the same site list before the first wave rather than after it.
The structural differences that decide whether a switch is worth starting.
Swipe the table sideways to see every column.
Vidan AI details come from Vidan's own site, read on August 14, 2026. The blank cells are absences on its public pages rather than gaps in this research, and they are the first questions to put to any vendor in writing, this one included.
A rollout that keeps coverage live throughout. Most sites go live inside six weeks.
Inventory the fleet per site: manufacturer, model, resolution, codec and network path. Any ONVIF or RTSP stream connects to the Intelligent Video Recorder as it is, and analog cameras behind a legacy NVR come in through it, so this is a coverage map rather than a replacement list. Then write down every detection currently running and every one your team asked for and did not get. That second list is the real subject of the comparison, and it is usually longer than anyone expects.
Run one site live on both at once, with nothing switched off. Pick two detections from the outstanding list, one that maps to a pre-trained agent and one that does not, and build the second in Iris during the pilot. That single exercise answers the question this page exists for, which is not whether a platform can detect something specific, but how long it takes to go from asking to having it.
Move site by site rather than estate-wide, keeping the existing detections live at each site until its replacement has run a full week. Cameras do not move and cabling does not change, so a site cutover is a configuration change plus an IVR. Where the current deployment holds any video or event history, agree the export format and the window in writing before the notice period starts rather than after.
Once coverage is stable, the work moves from parity to what a bespoke deployment could not scale to: pre-trained agents across security, safety and operations on the same cameras, Iris detections built by the people who noticed the problem, and a decision about what fires on site when nobody is watching. This is where the request queue from the assess phase gets closed.
The six that come up in every one of these conversations.
Start with your own paperwork: the end date, the notice period and whether the custom detection work was bought separately from the platform. Assess and pilot cost little and run alongside what you have, so use the overlap to compare and time any change to the date you find rather than paying twice.
No, and the plan is built to make that structural rather than a promise. The existing detections keep running at each site until the replacement has run a full week, the cameras never move, and cutover happens site by site. If a site fails its sign-off test, that site stays where it is while the others proceed.
Treat that as the acceptance test rather than an assumption. Take the live list into the pilot, map each one to a pre-trained agent where it fits, and build the rest in Iris on your own footage. If something does not carry across, you find out during a fortnight on one site rather than during a cutover, which is the whole reason the pilot exists.
Where video is stored is not publicly specified, so this is a question for your account team rather than something to assume either way. Get the storage location, the retention and the export format in writing during assess, then pull anything under legal or insurance hold out before the notice period starts. Treat that export as a deliverable with an owner and a date.
Possibly, and it is worth saying so. A platform that carries multi-site management, unlimited seats and an agent set spanning three teams is priced and built for an estate. If one site with two custom detections is the whole requirement and it works today, staying put is a reasonable answer. The case changes when a second site, a second team or a fifth detection arrives.
Anyone answering this without your site list is guessing. The number that usually decides it is not the license, it is what each additional detection costs in time and money. Ask both for a written answer on that, then quote the identical site list over three years with hardware and installation itemized.
Bring a camera list and we will tell you what works as it is.
Customer-reported outcomes from named Spot AI customers.
Staccato went from first conversation to full deployment across an 800-acre campus in seven weeks, on the camera infrastructure it already had.
Bridge33 Capital standardized video across 25 plus properties, each acquisition arriving with a different camera system, and cut footage search from hours to minutes.
The YMCA of Greater Richmond deployed 17 locations in two weeks and standardized retention across the estate.
"Within four minutes of the alarm going off, Spot AI gave us video footage of the incident on the responding officers' phones. We had five recoveries within the hour."
No. Spot AI works with any camera that speaks ONVIF or RTSP, whoever made it, and analog cameras connect through the Intelligent Video Recorder rather than being replaced. Vidan does not publish a camera compatibility statement, so confirm what your current deployment reads during the assess phase, but nothing on the wall has to move either way.
Most estates are live inside six weeks: a week to assess, a fortnight of pilot on one site, then site-by-site cutover. Sites go live individually rather than in a big-bang switch, so the timeline scales with how many sites you have rather than how many cameras.
Yes, and the plan depends on it. The pilot runs one site on both at once so detection quality and response can be compared on identical footage. The existing detections keep running at every site until that site's replacement has passed a full week of sign-off.
Two ways, and the pilot tests both. Some requirements map to one of the 15+ pre-trained agents already shipping across security, safety and operations. Anything that does not is built in Iris, in natural conversation, in about eight minutes. Bring your live detection list to the pilot and work through it item by item.
Vidan's model is that you define what to watch and it is built for you, which suits a specific requirement on a specific site. Spot AI ships a pre-trained agent set across security, safety and operations, keeps full-resolution video on the Intelligent Video Recorder in the building, adds Iris so your own team can define the next detection, and answers an incident through standard speakers already on site.