Interkey products
AI video analytics for industrial safety
A site has cameras and safety rules, but nobody watching every screen. SquintPRO is Interkey’s computer-vision platform for that gap: it analyses the CCTV you already own and turns detections into alerts, evidence and KPIs.
Orientation
Product and deployment characteristics
The whole page in one table, before the detail.
| Product | SquintPRO, an Interkey product, available now |
|---|---|
| Capability | Configurable detections, cross-camera analysis, text and image event search, incident records, dashboards |
| Cameras | Works with existing CCTV estates; compatible cameras are not replaced |
| Deployment | On-premise, cloud or hybrid; deployable in-Kingdom, including fully on-premise where footage cannot leave the site |
| Object detection accuracy | 96.7%, as stated in Interkey’s own product material (see the note below: validate on your own footage) |
| Alert delivery | Into the site’s existing VMS, alerting and incident workflow, not a new screen |
| Commercial model | Quote only: priced per site, camera count and use case |
The starting point
The operating problem
A large industrial site has hundreds of cameras and a control room with a handful of screens. The footage is recorded diligently and watched almost never, so the estate works as an archive rather than as monitoring.
Computer vision changes what it is for: software watches continuously and raises an alert when a defined condition occurs — someone in a zone without the required protective equipment, a vehicle where vehicles should not be.
Capabilities
What the platform does
Four capabilities, in the order a site uses them: detect, act, find again, report.
| Capability | What it does on a working site |
|---|---|
| Detection you configure | A site defines the conditions that matter, the zones they apply in and the thresholds, through the interface rather than in code. What is detectable depends on what the camera can see, which the survey establishes rather than assumes. |
| Alerts and incident handling | A detection raises a notification and opens an incident record with the video attached, routed into the tools the site already runs, so an event is reviewed, assigned and closed rather than only noticed. |
| Multi-camera analysis and search | Analytics run across many streams at once, following subjects between cameras. Past events are found by describing them or by supplying an image, so a timestamp-only archive becomes one an investigator can query. |
| Metrics and reporting | Detections accumulate into metrics and dashboards shaped to how the site already reports — a record by zone, shift and area rather than a monthly anecdote. |
On the 96.7% figure.
Data stays put
What in-Kingdom processing actually means
Industrial video is sensitive twice over: it shows the site, and it shows the people on it. Three different things get called “the data” — the raw camera stream, the model’s inference output, and the detection record (timestamp, camera, zone, event class) — and each can be held to a different rule, so the architecture should say which lives where.
Deployments can run entirely in-Kingdom, including fully on-premise where footage must never leave the site network. Worker privacy is a design input rather than an afterthought: what is retained, for how long, and who can see it are decided with the site’s HSE and legal owners before go-live.
Starting
How a deployment starts, and what Interkey does on the ground
The entry point is a single site, a defined set of cameras and one or two detection cases with a measurable outcome. That produces a detection figure under your own conditions, which is the only number that should drive a wider rollout — including in preference to the reference figure above.
Saudi industrial conditions are part of the test, deliberately: dust on camera domes, midday glare and heat haze are exactly what a pilot should expose. Interkey has written up how to scope a pilot that proves something, including the success criteria worth insisting on with any vendor.
When this is the wrong fit: sites without usable camera coverage, or where nobody owns what happens after an alert. Detection only changes an outcome if a named person acts on it.
Interkey product
Built, deployed and supported by Interkey
Runs on existing cameras
Established by survey, not assumed
Riyadh delivery team
Survey, integration, tuning and operation
Next step
Scope a PPE detection pilot
Tell us the site type, the camera estate you already have and the PPE rules that matter most, and the reply comes from the team that will actually walk the site.