Recipes
Short, focused guides for common streaming intelligence patterns. Each recipe solves one detection problem with an interactive demo running real winkComposer nodes in your browser.
Change Detection
Three complementary approaches to the same fundamental question: has something changed?
Detecting Gradual Drift→
Spot a signal that drifts slowly off its setpoint — invisible to threshold alarms, buried in noise. A fast/slow crossover surfaces the trend while Page-Hinkley accumulates evidence.
Detecting Sudden Shifts→
Catch a signal that jumps to a new level. The Kalman filter fires when reality disagrees with its prediction — toggle between tracking the jump and rejecting it as an outlier.
Detecting Subtle Process Shifts→
Find a process that creeps off-target — no single reading trips an alarm, but the pattern is non-random. Four Western Electric rules fire in sequence as the deviation grows.
The right tool depends on the signal. Gradual drift needs evidence accumulation — patience. Sudden shifts need immediate detection — speed. Subtle shifts need pattern recognition — sensitivity. Some real systems need all three.
Signal Quality
Sometimes the problem is not that the signal changed — it is that it stopped changing. A frozen sensor reports stale data that looks perfectly valid.