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Applied computer vision

Vision AI

Cameras that understand.

You already have cameras. What you do not have is a camera that can tell you a forklift entered a pedestrian aisle, that the queue is eight deep, or that the seal on line three is drifting. We deploy vision models at the edge, on your hardware, so the video never has to leave the building.

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Video leaving your network

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Edge inference, no round trip to a cloud

Retention you control, not a subscription tier

Detection, tracking and zone logic running at the edge.

Capabilities

What we actually deliver

Detection & tracking

People, vehicles, tools and pallets detected and tracked across frames and across cameras.

Face & licence plate recognition

Recognition pipelines with an explicit enrolment process and a defensible retention policy.

Safety & PPE compliance

Helmets, vests, exclusion zones and man-down detection, evaluated continuously instead of on inspection day.

Counting & queue analytics

Footfall, dwell time, occupancy and queue length, aggregated to numbers rather than faces.

Visual quality inspection

Defect, presence and alignment checks on the line, trained on your parts and your lighting.

Edge GPU deployment

Jetson or RTX inference nodes sized to your stream count, with graceful degradation under load.

Typical stack

YOLO familyONNX / TensorRTONVIF / RTSPFrigateNVIDIA JetsonCUDAMQTTS3-compatible storage

Indicative, not prescriptive. The final stack follows the site survey — never the other way around.

Start here

Tell us what should be automatic.

Send a sentence or a specification — both work. You will get a straight answer about whether it is worth building, and roughly what it takes.

Vision AI — Cameras that understand. — Dot Check