Manufacturing — 100% inspection
Surface defects, out-of-spec dimensions, and mis-assembled parts caught right on the line. Every part, not a sample.
We turn the cameras you already have into smart sensors: defects, missing PPE, queues, and bottlenecks detected in real time — feeding your ERP, your dashboards, or your supervisor's phone. Built one timezone away.
Pick an industry and watch the model detect events on the scene and turn them into alerts and records — exactly what it would do on your cameras.
Simulation with illustrative data. In a real project, the model is trained on your cameras, lighting, and operating conditions. Want the deep dive? Read computer vision on the plant floor.
The same technology, aimed at each industry's concrete problem: quality, safety, shrinkage, or flow.
Surface defects, out-of-spec dimensions, and mis-assembled parts caught right on the line. Every part, not a sample.
Detects workers without hard hats, vests, or glasses, restricted-zone intrusions, and dangerous proximity to forklifts — with instant alerts.
Automated counting of parts, pallets, and boxes; load verification before the truck leaves the yard.
Empty-shelf detection in minutes, checkout queues that trigger opening another register, and hourly traffic patterns for staffing.
License plate reading, automatic gate logs, dwell-time tracking, and access monitoring without a manual checkpoint.
PPE compliance on site, access control for crews and machinery, and visual progress records against schedule.
These are industry- and vendor-reported ranges, not our client results and not promises. The pilot measures yours.
Human visual inspection checks samples; a vision model checks every part that passes the camera.
Vendor-reported reduction at plants that moved from manual supervision to automated detection with real-time alerts.
Industry-reported range for well-scoped quality inspection projects in manufacturing.
We review your cameras, lighting, and the exact problem you want solved — and tell you honestly whether computer vision is the right tool.
One line, one camera, one measurable problem. Fixed quote and success criteria defined before work starts.
The model is trained on footage from your actual operation, and alerts are wired into your systems: ERP, dashboards, or messaging.
Results are measured against the pilot's criteria. If the numbers hold, the system rolls out to more lines, cameras, or sites.
In most cases, yes. Modern IP cameras from an existing CCTV setup are usually good enough to start. During the free consultation we review resolution, angles, and lighting, and tell you honestly whether anything needs adjusting or adding.
We start with a free consultation and a scoped pilot with a fixed quote — one line, one camera, one measurable problem. You see real detections on your own footage before deciding whether to scale.
Not necessarily. Most projects process video on-site (edge processing), so only events and metrics leave the camera network — not the footage itself. The architecture adapts to your security and data policies.
We design these systems to detect conditions, not identities: a missing hard hat, a defective part, a long queue. No facial recognition, which keeps deployments clear of biometric-privacy laws like Illinois BIPA.
A well-scoped pilot is measured in weeks, not months. The goal is to get detections running on your own cameras quickly, then decide with data whether to roll out to more lines or sites.
Book a free consultation and we'll tell you what computer vision can detect in your operation — and what isn't worth automating.
Talk to us about your project