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Every part checked the same way, and every defect on the record.

Camera images from the line are compared against your tolerances. Defects are marked, parts are routed, and trends show up before scrap does.

All solutions
Visual inspection
Pass rate
97.2%
last 500 parts
Rejected
14
Top cause
Edge burr
D1D2D3
Part 48113: reject. Edge burr exceeds the 0.3 mm tolerance. Routed to rework.

Illustrative interface, sample data. Built around your systems on a real project.

From your data to a decision your team approves.

In

Your documents and systems

1

We set up image capture on your line and learn your tolerances from labelled examples.

2

Each part is checked, defects are marked on the image, and a pass, rework or reject call is suggested.

3

Inspectors review edge cases, and defect trends are reported by line, shift and cause.

Out

Your team reviews and approves

Manual inspection varies by person and by shift, and defect records live in notebooks. Problems are found after a whole batch has shipped.

What your team gets

  • Marked-up image for every flagged part

  • Pass, rework or reject routing

  • Defect trends by line and shift

  • Evidence file for customer audits

Straight answers.

Not here? Ask us directly. We reply within one business day.

get@sievetech.ca
Does it replace inspectors?

No. It handles the repeatable checks and sends edge cases to people.

Can it run on the factory floor with no internet?

Yes. Inference can run on a local GPU box beside the line.

How much training data does it need?

It depends on the defect types. We start with your existing records and measure before committing to more.

Have a workflow like this?

Tell us what slows your team down. We will tell you honestly whether software can help.