Turn sensor data into foresight with Signal Sphinx. Predict failures, uncover anomalies, and optimize reliability before problems arise.

By solving the long-standing problem of automated preprocessing in time series classification, our model attains leading accuracy results on the widely used University of California, Riverside benchmark archive, even on a modest computational budget.


Benefit from our high software development velocity, rapid progress, and quick turnaround.

Our experienced business team will tailor the technological solutions around your specific business requirements.
Contact us today to explore how you can make better sense of your existing sensor data. Are you interested in preventative maintenance, sensor calibration/drift, anomaly detection, fault prediction, or something else?