04

Vision and edge

Visual quality inspection

Detect, segment, and review defects or assembly conditions on representative production imagery.

Primary buyer: Manufacturing quality and operations teams
01Primary buyerManufacturing quality and operations teams
02Target outcomeEarlier, measurable defect detection with a controlled review path
03Useful starting pointCamera geometry, line conditions, representative good/defect examples, error costs, throughput, and reviewer workflow.
01

The real constraint

Camera position, lighting, occlusion, privacy, hardware, and field maintenance can matter more than model choice.

02

How we approach it

We define zones, events, error costs, edge/cloud boundaries, review, and installation ownership before scaling cameras.

03

How we prove it

Representative footage is segmented by difficult conditions and evaluated against the operator decision it supports.

Production system

Vision and edge

Images and video converted into measurable events, quality evidence, and operational decisions.

  • 01Camera and scene specification
  • 02Detection, segmentation, and tracking
  • 03Zone, event, and temporal logic
  • 04Edge inference and secure transport
  • 05Operator review, alerts, and drift checks

Typical fit

Earlier, measurable defect detection with a controlled review path

IndustriesManufacturingLogistics
TechnologyComputer visionEdge inference

FAQ

Questions before a pilot

These answers describe how we normally work. Only a signed agreement creates commitments. Website enquiry terms

01Do we need to replace our cameras?

Often not. An existing installation is usually workable once the angle, resolution, and lighting are known, and we assess that on footage from your actual site before anyone buys hardware. Sometimes a camera needs moving rather than replacing. Occasionally the honest answer is that the current view cannot support the measurement, which is far cheaper to learn in week one.

02Does someone have to come to our site?

We work remotely by default and footage is often enough. When a project genuinely needs eyes on the line, the yard, or the device, we can travel within the European Union. Travel is arranged and priced separately from the engagement rather than assumed into it.

03What about people appearing in the footage?

That is decided before any camera is used, not afterwards. Depending on what you need, it can mean processing on site so images never leave, discarding frames once the event has been extracted, or blurring at the point of capture. The privacy design comes first because it constrains the architecture.

Service focus

Catching the defect before it leaves the line

Vision on a production line is mostly a lighting, geometry, and sampling problem, and only then a model problem. We specify the capture conditions, build the detection against your own good and defective parts, and set the threshold using what a miss actually costs you versus a false alarm.

Built for
Manufacturing quality and operations teams
Designed to achieve
Earlier, measurable defect detection with a controlled review path

What you get

  • Camera, lighting, and capture specification
  • Detection trained on your own good and defect samples
  • Threshold set from your miss and false-alarm costs
  • Operator review screen and line integration

Need a different system?

Not quite your solution?

Explore nearby systems or bring the outcome, workflow, and constraints that do not fit a predefined category. Tandemora can scope a custom solution around the real operating problem.

Your version will have different constraints.

Bring the workflow, current system, available evidence, and the assumption you trust least. We will identify the smallest useful next step.

Discuss this system