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White Paper

AI-based visual inspection: Build or Buy?

Discover the advantages and disadvantages of developing your own AI-based solution for visual quality inspection in our white paper – and learn when it becomes strategically relevant.

Discover the advantages and disadvantages of developing your own AI-based solution for visual quality inspection in our white paper – and learn when it becomes strategically relevant.

Peter Droege, CEO and co-founder of Maddox AI, smiling in a head-and-shoulders portrait.

Peter Droege

CEO & Co-founder of Maddox AI

CEO & Co-founder of Maddox AI

CEO & Co-founder of Maddox AI

We often hear from customers that an internal solution already exists – but in many cases, these are not fully implemented or fail to meet expectations. With AI being a hype topic, many decision-makers allocate significant budgets to develop their own in-house AI solutions. However, even AI projects must deliver a positive return on investment. This white paper helps decision-makers assess when developing an in-house AI solution makes strategic and economic sense.

We often hear from customers that an internal solution already exists – but in many cases, these are not fully implemented or fail to meet expectations. With AI being a hype topic, many decision-makers allocate significant budgets to develop their own in-house AI solutions. However, even AI projects must deliver a positive return on investment. This white paper helps decision-makers assess when developing an in-house AI solution makes strategic and economic sense.

MLOps components: data labelling, defect definition, artificial data generation, ML code, model decay and drift detection.
MLOps components: data labelling, defect definition, artificial data generation, ML code, model decay and drift detection.
MLOps components: data labelling, defect definition, artificial data generation, ML code, model decay and drift detection.

Discover the advantages and disadvantages of developing your own AI-based solution for visual quality inspection in our white paper – and learn when it becomes strategically relevant.

AI in machine vision: Build or Buy?

AI in machine vision: Build or Buy?

AI in machine vision: Build or Buy?

Automated image processing has been a core component of industrial quality control for decades – typically based on traditional, rule-based systems and externally sourced software solutions. However, the increasing adoption of artificial intelligence is changing how many companies approach this area: internal development projects are receiving significant budgets to build proprietary AI solutions.
Whether this approach leads to lasting competitive advantages or inefficient use of resources depends on a range of strategic and economic factors.