Human error and fatigue
Attention drifts on a check that repeats every few seconds, and the last hour of a shift is not the first. The defects that get through are the ones nobody was still looking for.
Industrial intelligence
Quality, assembly, safety and process, inspected inline at line speed on every part, on the cameras you already have.
Attention drifts on a check that repeats every few seconds, and the last hour of a shift is not the first. The defects that get through are the ones nobody was still looking for.
A manual check runs at the pace of the person doing it. Once the line runs faster than that, inspection becomes the thing everything else waits for.
Two inspectors, two thresholds. The same part passes on one shift and fails on the next, and the rejection rate moves with whoever is on.
A defect found by the customer is a warranty claim, a recall, or an account that does not come back. It is the same defect that cost pennies to catch on the line.
Catch what the human eye misses, at production speed, on every part, every shift.
Cameras capture every part in real time as it moves down the line.
Models classify and detect anomalies, defects and missing components.
Alerts, rejection and reporting are triggered automatically.
Vision AI isn't only defect detection. Put the same deep-learning platform behind any camera and turn it into an intelligent sensor for safety, process, logistics and security.
Defects, surface flaws, missing components and dimensional checks: 100% inline, at line speed.
Confirm every fastener, clip, seal and connector is present and correctly placed before the part moves on.
Detect missing helmets, vests, gloves or goggles in real time and alert before anyone enters the line.
Watch restricted or hazardous zones and trigger an alert the moment a person or vehicle crosses the line.
Spot flame colour, fill levels, flow, spatter or abnormal machine behaviour that no fixed sensor captures.
Count parts, packs and pallets, sort by type or grade, and keep live stock and WIP counts automatically.
Read labels, lot codes, serials and barcodes to verify print quality and build a full traceability record.
Analyse operator movement and cycle steps to catch unsafe posture and standardise manual work.
Perimeter watch, unattended-object and abnormal-movement detection across the site, 24/7.
Deep-learning inspection runs inline, 24/7, on every part, with no sampling gaps and no inspector fatigue.
Your good and defective samples are gathered, and the defect classes that matter to your quality gate are labelled.
Deep-learning models are trained and augmented to handle lighting, orientation and rare-defect variation.
Accuracy, false-accept and false-reject rates are measured against your acceptance criteria before go-live.
The model runs inline on the edge device, inspecting every part and triggering sort/alert actions.
New edge cases are fed back and the model is retrained, so accuracy compounds over time.
Illustrative live figures from a sample deployment.
Vision AI isn't a bolt-on island. Every defect and image flows into the same intelligence layer as your machines, so quality sits beside OEE and downtime in one view.
Four kinds of line, one reason for each: the thing that decides pass or fail is too small, too fast or too repetitive for an eye to catch every time.
Panels, welds and machined parts, where a surface flaw not found on the line is found by the customer.
Assemblies where what decides pass or fail is smaller than anyone can reliably see, shift after shift.
Regulated lines where every unit has to be checked and the check has to be evidenced, not asserted.
The last gate before a pallet leaves, where a wrong code or a broken seal travels the whole way downstream.
Often far less than expected. Your existing good and defective samples are the starting point, augmented and refined with live feedback from your line.
In many cases yes. Where lighting or resolution needs improvement, the right camera and optics are specified so detection stays reliable at line rate.
The part is flagged and can trigger automatic sorting or rejection, an operator alert, and a traceable record that feeds straight into the quality module.
Anywhere with a camera. The same deep-learning platform sits behind cameras for safety and PPE checks, restricted-zone monitoring, counting and sorting, code reading and perimeter security, not just the quality gate.
Send us a sample use case and we'll assess it on your own parts and tell you what is achievable.