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Who we build for

AI for Security operators

Security work sets a harder test than most AI deployments: the system has to be right while something is happening, on live feeds, at a rate of alerts your control room can actually act on.

That last constraint governs everything. A camera watching a busy site produces tens of thousands of judgements an hour, and at any realistic accuracy an untuned system floods the room and gets switched off. So the engineering effort goes into the rules as much as the models — how long a condition must persist, which zones and hours apply, how many frames confirm it — and into per-camera and per-operator records of what was flagged and what was done about it.

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Services that apply

The services security operators commission most often, grouped by whether they run live or over recorded material. Each links to its own page with the models, hardware and stream capacity behind it.

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Live feeds

Detection that must keep pace with the camera so an operator can intervene.

Recorded material

Reviewing footage after the fact — for investigation, evidence and audit.

  • General object detection and tracking

    Following a vehicle or person through hours of footage across cameras, instead of scrubbing timelines by hand.

  • Video semantic search

    Finding the moment by description — a described vehicle, a described action — with the file and timecode returned.

  • Crowd counter

    Density and build-up analysis at events, including the dangerous concentrations a total headcount hides.

  • People entrance / exit counting

    Footfall and flow reconstruction from recorded views for post-incident review.

  • Video OCR / text recognition

    Plates, markings and signage captured from footage with the time and position they appeared.

  • Video upscale resolution

    Making low-resolution footage viewable for briefing. The added detail is reconstructed, so it is presentation material and not evidence.

  • Face restoration

    The same caution applies more strongly: restored faces must never be used to identify anyone.

Identity, where lawful

Recognition is regulated in most jurisdictions. We deploy it only with a lawful basis, retention limits and notice settled first.

  • Face detection / face count

    Finds and counts faces without identifying anybody, which answers many questions on its own and carries far lighter obligations.

  • Face verification (1:1)

    Confirming a pass holder against their enrolled photograph — a single comparison, not a database search.

  • Face recognition

    Matching against an enrolled list, with the threshold set against list size and an operator reviewing uncertain matches.

  • Speaker recognition / verification

    Confirming a caller’s identity by voice, with a liveness check where it controls access.

Audio and reporting

What was said, and turning a shift’s activity into a record.

Bring your own model

Operators running a detector built for their own site — a specific vehicle class, a particular piece of equipment, a behaviour your analysts defined — can run it on Super-GPU infrastructure alongside our services, on the same streams.

We help you select the right hardware, containerize and deploy the workload, build the processing pipeline and define the infrastructure required to scale it.

Your model. Your data. Your deployment choice.

Bring your existing GPU containers

We support standard Linux GPU workloads including:

  • Docker
  • OCI images
  • NVIDIA CUDA
  • vLLM
  • TensorFlow
  • PyTorch

and other GPU-enabled environments. Images can be uploaded directly or pulled from registries including AWS ECR, Docker Hub, GitHub Container Registry, Google Artifact Registry, Azure Container Registry, Harbor and private registries.

Where it runs

Security footage rarely has permission to leave the network it was captured on, and the deployment options reflect that.

On premises, in your AWS account, GCP project or OCI tenancy, on Super-GPU Cloud, or across a hybrid environment that keeps latency-sensitive work local and reaches for cloud GPU capacity when scale demands it. You control where data is processed, stored and retained.

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