Analyzing and sorting waste on a new level
From material classification to object detection with our AI systems
Our value added
Our Deep Learning algorithms detect way more than just the material of waste pieces
Data based process optimization (e.g. purer sorting, new streams)
Elimination of hazardous substances and lower insurance fees
Cost savings via automatization
Use Cases
Sort Inspector
Detailed analysis of material flows (e.g. purity, unwanted objects etc.) in sorting plants.
+ Process monitoring & optimization based on facts
+ Regulating other machines
Bundle Inspector
Digital input quality control of bundles from suppliers.
+ Automated process instead of manual samples
+ Optimized pricing of suppliers due to quality tracking
Further Use Cases
Your Use Case
Capturing much more information on objects in your waste streams enables unprecedented use cases in waste management.
Whether you recycle paper, WEEE, LVP, residual waste, commercial, glass, etc., let us solve your problems together.
Let us share our experiences!
The AI sorting machine
The Future of Sorting
1. Material and object properties are detected by visual sensoric and AI
2. Machine learning algorithm controls nozzles to direct objects in the correct stream
3. Sensoric in stream channel sends feedback to algorithm for self-learning optimization
+ Substantially less impurities
+ For 8 different streams only 1 machine is needed instead of 7
+ New material streams possible (e.g. food & non-food)
Team
Nathanael Laier
Product Lead
Johannes Laier
Finance Lead
Martin Körner
Business Development Lead
Christian Schärf
Technology Lead
Tobias Scheuer
Head of Data
Simon Diener
Deep Learning Engineer
Our Partners & Supporters
We are funded by
Our Office
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