AI-driven machine tuning for efficient, high-quality production. Lower expenses, reduce waste, and let your experts focus on critical tasks.

Start optimizing in days. Our AI adapts quickly, delivering measurable improvements with minimal setup.
Combine expert insights with AI. Continuous feedback ensures ongoing process optimization.
Automatically adjusts to new products and process changes, maintaining quality and efficiency.
Achieve results with minimal data. Only essential information is collected, reducing complexity and cost.
aiXopt Setup automatically finds optimal process parameters for your machines before and after delivery
Automatic - ai powered - data generation and evaluation for the fastest way to optimal parameters, minimising turnover times
Enable the end-user - AI empowers process experts to tune their machines without deep machine knowledge, minimizing service effort
High product variability - AI learns from the past, finding fast parametrizations even for new machines
aiXopt Adapt takes your production to a new level. Modern machine learning to optimise your process parameters in the loop.
aiXopt automatically optimises productivity, error rate, energy usage, ...
The AI system integrates your experts' knowledge preserving the knowledge of decades.
AI detects changes in raw materials, products, environment or wear and keeps production running optimally.
The aiXopt optimization core keeps your plant operation within specification always,automatically, while minimizing opEx
Free up your experts by giving them powerful AI support and leave parameter selection to us.
Our software directly leverages your experts’ know-how and keeps all ai decisions explainable
The aiXopt optimization core works just as well with visual inspection as with sensor data





David Stenger holds a PhD in control engineering from RWTH Aachen University focusing on the optimisation of parameters in various control engineering applications. He looks at 10+ years of research in the area resulting in 14+ publications. David is responsible for technological topics.
Tim Reuscher also holds a PhD in control engineering from RWTH Aachen University. Previously he worked in leadership roles resulting in 3 years as Head of, responsible for up to 16 FTE PhD candidates, including strategic and budgetary planning. Tim is responsible for organisational topics and external representation,

In a fast living world of AI, the connection to cutting edge research grows increasingly important. We value this by keeping a close relationship with leading researcher, scientific advisor and Co-Founder Prof. Sebastian Trimpe. The RWTH Aachen University Professor leads Institute for Data Science in Mechanical Engineering (DSME), researching into the future of AI in mechanical engineering. He is also Executive Director of the RWTH AI Center.
Based on our experience, we help define: Optimization goals, Safety parameters, Visualization, Interfaces etc. All results are transferred to a simulation mockup that allows us to validate the workshop results.
The solution is just one API call away. We position ourselves within the supervisory layer, obtain quality data and communicate with the control layer or SCADA systems.
Over 10 years of cutting-edge research in AI and Optimisation allows us to provide significant improvements to existing production systems. Based on our prior use cases, we can show:
Reduction in Setup Times
Reduction of Waste
Reduction of production errors
Potential of your production