Lightweight, high-accuracy real-time prediction AI that runs on small devices.
No cloud required. No GPU required. Predict unmeasurable values,
detect anomalies, and forecast remaining useful life from existing sensor data.
Entrox Systems is a spin-out project from the DLR German Aerospace Center. We are developing reservoir computing technology from the research lab for real-world industrial applications.
Based in Germany, developing cutting-edge prediction technology for industrial sites worldwide.
Industrial sites generate diverse time-series data from sensors and equipment. Our AI learns patterns from even small amounts of time-series data, enabling real-time prediction of hard-to-measure values, anomaly detection, and remaining life forecasting.
Deployable as software on your existing equipment — from industrial PCs to microcontrollers. No special hardware required.
Runs on small, low-cost devices. No cloud connection required — your data stays on-site.
Training completes in seconds. Quickly adapts to new environments and starts running immediately.
As lightweight as traditional methods, with accuracy rivaling deep learning.
Builds optimized models per site and use case. Flexibly handles high-mix, low-volume production.
Model structure is fully visible as mathematical expressions. Prediction rationale can be traced and verified.
Combine existing physics equations or empirical formulas with AI that corrects the residual error.
Addressing the full spectrum of industrial prediction challenges.
Real-time prediction of hard-to-measure parameters from existing sensor data
Replacing lab wait times and costly analyzers with real-time estimation.
Learns "normal behavior" of equipment and detects early signs of anomalies
Detecting early signs of degradation — trained from normal data only.
Predicts remaining useful life from sensor data to enable planned maintenance
Planning maintenance based on actual condition, not fixed schedules.
Visualize which variables, at which time lags, and through which nonlinear relationships affect your process — expressed as mathematical equations
Validating expert knowledge and supporting knowledge transfer with data.
Real-time prediction of hard-to-measure quality parameters. Reduce analysis wait times and enable early defect detection.
Early detection of anomalies in pumps, compressors, and more. Prevent unplanned downtime and reduce maintenance costs.
Predict quality and efficiency from operating conditions. Reduce trial-and-error and digitize expert knowledge.
Build individual models per product and line in minutes. Flexibly adapt to high-mix, low-volume production.
Understand which variables, time lags, and their interactions influence predictions. Identify drivers behind anomalies and quality variations.
AI, Mechanical Engineering, Business Development
AI, Algorithm Development
AI, Software Development
We co-develop solutions through proof-of-concept projects with leading technology partners.
Our founding research group is based at DLR, the German Aerospace Center, conducting international collaborative research.
Published in IEEE, Elsevier, Springer, and other leading journals.
An integrated development pipeline from research to real-world deployment.
We conduct small-scale pilot projects using your real data to demonstrate effectiveness in your actual environment. Ultimately, you get deployable AI software optimized for your specific process, running on your existing devices. Get in touch to discuss your use case.
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