What Hanwha Vision's own manual says Wisenet WAVE does not do, or only does when the hardware allows it, written for IT and security teams sizing their own video servers. Every constraint below carries the documentation behind it, the operational impact, and the workaround.
Every constraint below comes from Hanwha Vision's own Wisenet WAVE manual and support portal, checked on August 14, 2026. That date is older than this page on purpose: hanwhavision.com could not be re-read on August 17, because every path returned a redirect rather than a page, so this page carries the date the evidence was actually gathered rather than claiming a check that did not happen. Where Hanwha documents nothing, this page says so rather than guessing. Spot AI sells a competing platform, so nothing here rests on an anonymous source or an aggregated user rating, and two things are stated plainly before anything else: this page is about Wisenet WAVE, the video management software, not about Hanwha cameras, which are ONVIF devices that connect to Spot AI as they are and are compatibility partners rather than rivals. Nothing here should be read as a limitation of the hardware.
This is software documented like software: the device rules, the capacity ceilings and the exact actions a rule can fire are all in the manual. What the software itself understands about a frame is the part that is not.
A constraint list is only useful next to an honest account of the product.
Hanwha's support portal carries a compatible-devices list covering more than a thousand manufacturers and tens of thousands of devices, and WAVE detects ONVIF Profile S devices automatically in the resource tree, with RTSP and HTTP streams added by hand from the server. An IT team can hold a real mixed fleet against a real list rather than trusting the phrase open platform.
Recommended maximums are stated outright: 100 servers and 10,000 resources per system, 256 cameras per server and 1,000 users. That gives an engineer the numbers to size hardware before a purchase order, and gives a large estate a way to model its server count honestly rather than discovering it in year two.
Documented actions include Play Sound, Repeat Sound, Speak, Device Output for 30 seconds, Bookmark, Send Email, Show Notification, Show Text Overlay and Execute PTZ Preset. Clients run on Windows, macOS and Ubuntu Linux, on Android and iOS, and through the server web admin and cloud admin, so an operations team is not forced onto one operating system to run its own video.
Each one is a consequence of how the platform is designed rather than a defect. What matters is whether it collides with your starting point.
The AI analytics Hanwha publishes are camera-side features, and the software presents and searches what those cameras produce. What WAVE itself derives from a third-party stream is not publicly specified. The manual documents which devices can be added and what a rule can trigger, not what metadata arrives from a camera that is not Hanwha's.
On an estate assembled from four manufacturers over a decade, the detection quality varies camera by camera rather than platform-wide, and the oldest third of the fleet may contribute a stream and nothing else. A project justified by what the cameras will notice can end up funding a recording upgrade instead.
List the fleet by manufacturer and model and mark which cameras carry analytics of their own today. Then ask Hanwha, in writing, which of that metadata WAVE surfaces and searches per manufacturer, and pilot on the mixed subset rather than on the newest cameras in the building.
Hanwha documents the license types by name in its support portal and licenses are counted per recorded channel. The manual states the recommended maximum of 256 cameras per server, with 100 servers and 10,000 resources per system, which places the recording hardware on the customer's side of the line by design.
A 600-camera estate is at least three recording servers before anything else is decided, each one specified, racked, patched and eventually refreshed, with channel licenses counted on top. The software decision turns out to be the smaller half of the three-year number.
Size the channel count against a three-year camera plan rather than today's, and confirm the license type each figure belongs to in writing with the reseller. Put the server hardware and its refresh cycle on the same three-year sheet as the licenses, so a comparison against a hosted platform is like for like.
The sound actions in the rules engine require a device that supports two-way audio, and accept WAV, MP3, OGG or WMA files up to 30 seconds. Device Output fires for 30 seconds. Whether a given site can speak at all is therefore a hardware question rather than a software one, and the manual is explicit about the dependency.
Two sites on the same license can behave completely differently after hours: the one with two-way audio cameras at the gate can talk, and the one without has a notification. On a chain of twelve locations that is a site-by-site audit, not a configuration screen.
Audit which cameras support two-way audio before the software evaluation, and mark the response points that matter rather than every camera. Where a site already runs a public address system, ask each platform on the shortlist which of them drives standard speakers without another device at each point.
Hanwha states how the list is built, which almost nobody does: it is compiled from devices found on WAVE systems where the user allowed device specifications to be reported back. So a listing means the device has been seen working somewhere, which is a different claim from a tested and supported commitment at a specific firmware version.
A procurement team that treats the list as a compatibility matrix can arrive at commissioning with a camera that appears on it and still behaves differently on the firmware your estate happens to run. The honesty of the caveat is a strength; acting as though it is not there is the risk.
Check model and firmware version together, and ask for a supported statement on the exact combinations that carry your critical views. Keep a small replacement line in the budget for whatever appears only as a report, and validate those cameras first in the pilot rather than last.
Hanwha publishes 100 servers and 10,000 resources per system, 256 cameras per server and 1,000 users as recommended maximums rather than hard limits, with performance depending on the system configuration. That is the honest way to state a ceiling, and it means the numbers are a starting point for a design review rather than a promise of headroom.
A design that lands 250 cameras on one server sits at the published ceiling on day one, so the next store, the next dock camera or a resolution change becomes another server plus its licenses. Growth arrives as a capital request rather than as a setting.
Design at roughly 70 percent of the published ceiling and write the growth trigger into the design document, so the second server is a scheduled purchase rather than a surprise. Ask Hanwha or the integrator to state the configuration their recommended maximum assumes, including resolution, frame rate and retention.
The same five constraints in one view, sized to paste into an evaluation document.
Swipe the table sideways to see every column.
Hanwha Vision data comes from Hanwha Vision's own Wisenet WAVE manual and support portal, checked on August 14, 2026, the last date the site could be read. Gaps are marked as not publicly specified.
If the requirement is a capable video management system on servers you specify, with retention, network and access under your own control, and a published device list to hold a mixed fleet against, most of the constraints above stop applying. You are buying recording infrastructure you own on purpose, and Hanwha documents it in more engineering detail than most of this category manages, down to the client platforms and the exact actions a rule can fire.
Spot AI starts from the other end of the stack, which is why its constraint list looks different. The detections come with the platform rather than with the camera: 15+ pre-trained Video AI Agents cover vehicle break-in, fire, cash register theft, after-hours intrusion, personal protective equipment, forklift near-miss, falls and crowding in hazard zones, and Iris builds a custom detection in natural conversation in about eight minutes. A mixed fleet gets one detection standard rather than one per manufacturer.
The camera side stays open, and Hanwha cameras are among the ones that connect as they are. Any ONVIF or RTSP IP camera works at full functionality and legacy analog comes in through the Intelligent Video Recorder, so the estate does not split into a modern half and a stream-only half. Full-resolution video stays on the IVR in the building and only event metadata crosses the network, and response runs through talk down, strobes and horns on standard speakers already installed.
The useful question is not which platform documents itself better, but whether the intelligence you are buying lives in the software you chose or in the cameras somebody chose years ago.
None of that makes Spot AI the right answer for every buyer. Hanwha publishes a compatible-devices list covering more than a thousand manufacturers where Spot AI states compatibility by protocol rather than by model, and it publishes capacity numbers per server that Spot AI does not publish at all, so an engineer who wants to size hardware from a document will find more of it on Hanwha's side. Spot AI is a video AI platform rather than a video management system you host yourself, there is no desktop client for Windows, macOS and Linux to compare against WAVE's, and access control and sensors arrive through integrations. A constraint list earns its keep by holding each platform's shape against your starting point.
A live pilot on your cameras answers in a week what a spec sheet cannot.
Customer-reported outcomes from named Spot AI customers.
Silver Bay Seafoods replaced fragmented legacy camera systems across 22 locations, including remote Alaska facilities, and lifted operational efficiency 15%.
Cambridge City cut footage search from two hours to 30 seconds after consolidating seven municipal locations on one platform.
Liberty-Perry School District resolves an incident in about five minutes, after evaluating ten systems before choosing Spot AI.
"With Spot AI, we're talking about five minutes, tops, to resolve an incident now."
Five, all documented: the AI analytics Hanwha publishes run on the camera and what WAVE derives from a third-party stream is not publicly specified; licenses are counted per recorded channel while the recording servers stay on your side at a recommended maximum of 256 cameras each; sound actions need a device that supports two-way audio; the compatible-devices list is compiled from devices reported by WAVE systems rather than certified; and the published capacity figures are recommended maximums rather than hard limits.
Yes, and unusually well. Hanwha documents that ONVIF Profile S devices are detected automatically and appear in the WAVE resource tree, that RTSP and HTTP streams can be added by hand from the server, and publishes a compatible-devices list covering more than a thousand manufacturers. The constraint is not access to the stream, it is what the software derives from a stream a Hanwha camera did not produce, which is not publicly specified.
The analytics Hanwha publishes are camera-side. WAVE presents and searches what the cameras send it, and the manual documents the rules engine rather than a detection set: Play Sound, Repeat Sound, Speak, Device Output for 30 seconds, Bookmark, Send Email, Show Notification, Show Text Overlay and Execute PTZ Preset. A plant that wants personal protective equipment, forklift proximity or dock dwell on the same feeds is looking at a second product above the video management system.
Hanwha publishes a recommended maximum of 256 cameras per server, with 100 servers and 10,000 resources per system and 1,000 users, and states these are recommendations that depend on the system configuration rather than hard ceilings. Treat them as inputs to a design review: ask which resolution, frame rate and retention the recommendation assumes, and design below the ceiling so growth does not force an unplanned server.
It depends which layer the project is buying. If the goal is recording infrastructure you own and control, WAVE is hard to fault and documents itself better than most. If the goal is named detections across a mixed fleet and something happening on site when one fires, a camera-agnostic platform such as Spot AI fits: any ONVIF or RTSP camera connects as it is, Hanwha cameras included, 15+ pre-trained Video AI Agents run across the whole fleet, and full-resolution video stays on the Intelligent Video Recorder on site.