Predco
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Product · Camera Intelligence

Turn every existing camera into a smart sensor that produces structured insight.

Context AI is the vision intelligence layer behind Predco. It runs on your existing IP cameras — no rip-and-replace — and produces structured events your EHS, Quality, and Operations teams can actually act on.

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CategoryCamera intelligence
SensorsExisting RTSP / ONVIF cameras
InferenceEdge GPU appliance
DeploymentOn-prem · Air-gap supported
Replace with real photography for this page
Detection latency <400 ms
Camera reuse 100%
01 / Core capabilities

Vision intelligence — designed for the realities of the industrial floor.

Most computer-vision systems were trained in research labs and bench-tested in retail. Context AI was built for variable lighting, dirty cameras, mixed shifts, and the noise that defines real manufacturing.

Existing cameras, new senses
RTSP / ONVIF support means your current CCTV becomes the sensor layer. No new cabling, no replacement cameras.
Multi-model vision
Detection, classification, segmentation, pose, OCR — across the same camera feed, in parallel.
Facility-tuned models
Models tune to your facility's lighting, palette, layout — accuracy compounds week over week.
Anonymity by design
Track events, durations, postures — never identities. Faces are blurred at the edge before frames leave the GPU.
Edge inference
Inference runs on a local GPU appliance per facility. Footage never leaves the plant unless you explicitly enable it.
Structured events out
Events emit as JSON over webhook, MQTT, or Kafka — ready for your EHS, MES, or analytics stack.
02 / Architecture
GPU edge → plant aggregator → enterprise events.

Context AI is a three-tier system. Edge GPU appliances run inference at the line, a plant aggregator handles fusion and rules, and an enterprise tier routes events into the systems that actually receive them.

  • Edge: NVIDIA Jetson Orin / IGX or customer-supplied GPU
  • Plant aggregator: containerized Kubernetes-ready stack
  • Event bus: MQTT, Kafka, REST webhook
  • Per-camera FPS, resolution, and model assignment
  • Air-gap-capable — no internet egress required
Replace with: product architecture / dataflow diagram
03 / Use cases

What customers run on Context AI.

Every Predco vision-based solution — Shopfloor Safety, Worker Productivity, Quality Inspection, Environmental — runs on the same Context AI core.

UC.01
PPE & exclusion zone monitoringHelmet, vest, glasses, exclusion zones, forklift lanes — across all camera feeds.
−72% incidents
UC.02
Line-side quality inspectionDefect detection, completeness checks, assembly verification at line speed.
<0.4% false reject
UC.03
Productivity analyticsCycle time, dwell, idle, queue depth — anonymous and continuous.
+12% throughput
UC.04
Headcount + musteringZone-level occupancy, evacuation verification at assembly points.
100% coverage
UC.05
Environmental incident detectionSpill, leak, smoke, unsafe storage detection — passively monitored.
<60 s detection
04 / Technology stack

What it runs on

Modular components — adopt the whole platform or just the pieces you need.

Computer VisionPose EstimationAnomaly DetectionMulti-camera TrackingOCR / Text in SceneGeo-Tagging / FencingEdge GPU InferenceStream ProcessingEvent Bus (MQTT / Kafka)Model RegistryMLOps PipelinePrivacy-Preserving Models
05 / Outcomes

What Context AI delivers across deployments.

97.4%
Detection accuracy
Across PPE + behavior classes after 8 weeks of facility tuning.
<400ms
End-to-end latency
From frame ingest to event emitted.
100%
Camera reuse
Zero replacements required across deployments.
0
Data egress required
Air-gap deployments fully supported.
06 / Deployment

How it ships

Designed for industrial environments — on-prem, edge, or cloud.

Form factorEdge GPU appliance (1U / 2U) + plant aggregator (VM or container)
Edge hardwareNVIDIA Jetson Orin, IGX, or customer-supplied GPU
Camera supportRTSP / ONVIF — Hikvision, Dahua, Axis, Bosch, Pelco, etc.
Frame rateConfigurable per stream — typically 5–15 FPS for safety, 25–30 FPS for line QC
NetworkPlant LAN only — internet egress optional
Identity & accessSAML 2.0, OIDC, Azure AD, Okta
Security postureSOC 2 Type II in progress · IEC 62443-compatible architecture
Typical pilot4–6 weeks, 4–8 cameras, single use case
Available for new deployments — Q2 2026

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Bring AI-powered compliance to your manufacturing operations. A 30-minute call with our team — no slideware, just a working walkthrough.

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4 hrs
Avg response time
6 wks
From kickoff to live pilot
SOC 2
Enterprise security posture