Measure deviation between sensor outputs and trusted reference values across robotics, industrial, automotive, aerospace, and scientific systems.

Verify whether incoming signals are plausible, calibrated, synchronized, complete, traceable, and consistent with trusted baselines.

Identify calibration drift, bias, noise, timing errors, saturation, missing data, interference, and degraded signal quality over time.

Convert signal accuracy into confidence scores that downstream models, agents, machines, and operators can use when making decisions.