Computer Vision for Manufacturing, Retail and Supply Chain
From camera to decision in milliseconds. On-device. No cloud round-trip required.
Computer Vision for Manufacturing
Computer vision on the factory floor isn’t about having the best model, it’s about having a model that runs at the right latency, on the right hardware, connected to the right systems, in an environment your data centre engineers would never set foot in.
We design and deploy production computer vision systems for manufacturers — optimised for edge hardware, hardened for industrial conditions, and integrated with the operational systems that need to act on what the camera sees.
Two Use Cases We Deliver
Defect Detection & Quality Inspection
Automated visual inspection at line speed; detecting surface defects, dimensional variance, assembly errors, and packaging faults without slowing production. Deployed on NVIDIA Jetson Orin for real-time inference at the point of manufacture, feeding results directly into your quality management or ERP system.
- Surface defect and anomaly detection
- Dimensional and assembly verification
- Packaging and labelling inspection
- Real-time pass/fail with audit logging
- ERP and MES integration via OPC-UA or REST
PPE & Safety Compliance
Continuous, automated monitoring of PPE compliance and unsafe behaviour across production areas, without manual observation or after-the-fact review. On-device inference means no video leaves the facility, addressing data sovereignty and GDPR concerns directly.
- Hard hat, hi-vis, and glove detection
- Restricted zone and proximity monitoring
- Real-time alerting to supervisors
- Compliance reporting and audit trail
- On-device processing — no video sent to cloud
Technical Stack
- NVIDIA Jetson Orin — primary inference platform
- NXP i.MX 9x — constrained device deployment
- TensorRT and ONNX Runtime optimisation
- YOLO and custom model integration
- OPC-UA, Modbus, MQTT, REST
- EdgeOps inference observability
- On-premises — no cloud dependency
Why On-Device Matters
- Latency — sub-50ms decisions without a network hop
- Reliability — keeps running when connectivity drops
- Data sovereignty — video never leaves the facility
- Cost — no per-inference cloud billing
- GDPR — on-premises processing simplifies compliance
How an Engagement Works
Discovery Call
30 minutes with John to understand your production environment, the problem you’re trying to solve, and whether computer vision is the right tool for it.
Site Assessment
We assess your production environment — lighting, camera placement, hardware constraints, and integration points — and produce a scoped delivery plan with hardware recommendations.
Pilot Deployment
A focused, time-boxed pilot on a single line or use case — proving the system works in your environment before committing to full deployment. Typically 4–6 weeks.
Production Rollout
Full deployment across lines and sites, with EdgeOps inference observability integrated from day one — so you have visibility into model performance, hardware health, and drift from the moment it goes live.
Ready to put computer vision to work on your production line?
30 minutes with John Ward. No sales deck — just an honest conversation about your production environment and whether we can help.