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Custom engineering service / Applied AI & production engineering

Make one visual production check measurable, traceable and reviewable.

For one product family and one visible criterion, we engineer the imaging setup, inspection pipeline, evidence record and operator-review workflow, then validate performance against customer-approved decisions.

Discovery, pilot and staged implementation

AI production inspection
A camera-based inspection station with traceable evidence and human quality review.

01 / Udfordringen

AI production inspection

A model cannot compensate for undefined acceptance criteria, unsuitable lighting, poor product presentation or missing examples. The visible condition, line speed, variants and cost of missed defects versus false rejects must be made explicit.

Den tekniske tilgang

Discovery covers lighting, optics, camera position, triggering and representative data. Suitable computer-vision methods, AI models and explicit rules are combined in a versioned pipeline. Every result retains its image, product or batch identity, inspection configuration and review outcome.

02 / Customer benefit

Customer benefit

  • 01Support consistent execution of one agreed visual check
  • 02Give quality staff evidence for reviewing suspected defects
  • 03Connect observations to products, batches and production orders
  • 04Investigate recurring visible defect patterns in operational context
  • 05Add product variants and inspection checks through a measured process

Good fit when

Good fit when

  • Products have a repeatable visible quality or assembly check
  • Labels, packaging, component presence or surfaces are inspected
  • Conforming and defective examples can be collected and labelled
  • The inspection point, cycle time and acceptance owner are defined
  • Production records expose the identifiers needed for traceability

03 / Delivery workflow

Pilot delivery path

Discovery covers lighting, optics, camera position, triggering and representative data. Suitable computer-vision methods, AI models and explicit rules are combined in a versioned pipeline. Every result retains its image, product or batch identity, inspection configuration and review outcome.

01

Specify one visible criterion

02

Engineer imaging and reference data

03

Build inspection and review workflow

04

Validate misses, false rejects and cycle time

Initial pilot deliverables

  • Inspection specification and imaging feasibility assessment
  • A labelled reference dataset with separate validation examples
  • A prototype pipeline and operator review interface
  • Versioned evidence linked to product or batch identifiers
  • A validation report and staged implementation recommendation

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