Starting hypothesis: In order to build meaningful AI solutions you (at least) need 3 different skill sets
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Deep expertise in AI
Productization experience
Business Know-How
Problem: Quality control is still oftentimes performed manually creating several pain points
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High labour costs
Potentially long inspection times
Inconsistent inspection results
Non-transparent / non-digital
Work is exhaustive
High re-training effort due to churn
Solution: Modern Computer Vision algorithms can automate the quality control process addressing these pain points
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+
Low labour costs
Inspections need <1 second
Consistent (=learned) quality standard
Transparent & digital documentation
The model doesn’t tire
Model learns through feedback
We have built a product that aims to address these pain points through various features…
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On prem Cloud
Ruggedized TX2
Industrycamera
Industrymonitor
Inspect parts on the edge
Label new data
Review model
Generate automatic reports
…while leveraging human expertise to continuously learn and improve the inspection quality
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L7 quality control solution
Client
Layer7 AI
Product Deployment Image Review
Model Refinement FeedbackModel improvement
Error classification
Clients can test our solution free of charge – costs are only incurred if we manage to “solve” the specific use-case
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Hardware Installation
Data collection & Model training
Model Evaluation
Use-Case Identification
Model Integration & Improvement
2 31 4 5
Free of chargePerformance
based purchase
Visual quality control market
The current visual quality control market can be broadly divided into three sub-segments…
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Traditional visual quality control
• Mostly based on classic rule-based systems
• Often used for simple relatively static use-cases – e.g. measuring & counting
100% manual visual quality control
Partial manual visual quality control
• Based on the human visual senses
• Often used for complex use-cases with a high variability –e.g. surface/texture inspection
• Based on the human visual senses
• Often used for complex use-cases with a particularly high throughput rate
Visual quality control market
…while most existing players operate with a clear focus on traditional visual quality control
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Traditional visual quality control
100% manual visual quality control
Partial manual visual quality control
New emerging market
No clear market leader has emerged in this new market as “one-size fits all” solutions do not exist in an AI world
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That‘s the reason why we decided to start our company in the Cyber Valley – Germany‘s home of modern machine learning
A well functioning AI model for one use-case…
…will most likely not translate to another inspection case
Most functioning AI-based quality control models still need to be customized and tailored by experts, which are hard to come by
According to Element AI, there are only 10,000 real AI experts worldwide
Thank you for yourattention
Peter DroegeCEOE-Mail: [email protected]: +49 159 01479983
Website: https://www.layer7.aiLinkedIn: https://www.linkedin.com/company/layer7-ai/Twitter: https://twitter.com/layer7aiMedium: https://medium.com/layer7-ai
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