An optimised edge AI runtime and appliance line that runs 3Cubicles models on-site with millisecond latency, offline resilience, and dramatic bandwidth savings.
3Cubicles Edge moves intelligence to the camera side of the network. Streams are decoded, analysed, and reduced to compact metadata locally, so sites stay operational without connectivity and only the signal travels upstream. Fleet tooling keeps hundreds of nodes updated, secured, and observable.
Appliances or your own hardware enrol automatically and pull their assigned configuration.
Streams are analysed on-device; only events, metrics, and relevant clips leave the site.
Monitor health, update models, and roll out policies across the whole fleet from one console.
Enable the capabilities you need per camera, zone, and schedule. Each produces structured events that flow into rules, dashboards, and integrations.
Optimised execution on GPU, NPU, and VPU accelerators with automatic precision selection.
Hardware video decode for dozens of concurrent H.264/H.265 streams per appliance.
Quantisation, pruning, and compilation pipelines that shrink models without sacrificing accuracy.
Store-and-forward buffering keeps analytics and alerts running through network outages.
Zero-touch provisioning, staged rollouts, and rollback for models and firmware.
Secure boot, encrypted model storage, signed updates, and hardware-backed identity.
Send metadata, thumbnails, or clips depending on policy and link quality.
Seamless aggregation into 3Cubicles Core for cross-site analytics and reporting.
Pipelines, substations, and rural facilities with intermittent connectivity.
Hundreds of stores running identical analytics with centralised updates.
Deterministic latency for safety-critical detections near machinery.
Traffic analytics at intersections without backhauling raw video.
Perceive. Understand. Act.
Request a demo and we will walk through the capabilities, deployment options, and integrations that fit your environment.