Readi’s machine learning model is calibrated based on an anonymized and growing database of 10 million sleeps. These sleeps were recorded by wearables worn by shift workers around the world in industrial environments.

Combined with de-identified data on shift schedules, demographics, and survey responses, these data enable an unparalleled ML engine to predict a worker's sleep history without requiring the use of wearables. The sleep predictions then serve as an input into our fatigue prediction model, SAFTE.

The SAFTE Fatigue Model was developed by the Walter Reed Army Institute of Research at the U.S. Army Medical Research Development Command. It has been extensively validated by the U.S. Department of Transportation, Federal Aviation Administration, and numerous other organizations.

The SAFTE Fatigue Model is exclusively available from Fatigue Science and its affiliates.

We know intuitively that a lack of sleep causes fatigue, but knowing one’s sleep quantity is only one of the many factors necessary in order to create an accurate fatigue prediction.

Accordingly, the SAFTE Fatigue Model accounts for a robust array of relevant sleep factors, including acute sleep interruptions, cumulative sleep debt, and the consistency of sleep onset and wake times, and circadian disruptions that influence a change in cognitive function.

The ReadiScore is the SAFTE Model’s output, a prediction of hour-by-hour changes in cognitive effectiveness, reaction time, and lapse likelihood throughout the course of the day or night.

Fatigue progresses in a predictable manner, and the SAFTE Model considers not only cumulative sleep history, but also factors such as the internal body-clock and and seasonal light exposure based on one’s general geographic location.

The ReadiScore has not only been validated in the lab; it has also been proven in real-world industrial environments as a predictor of operator safety and performance. Customer case studies have proven that Readi can:

• Reduce telematics events by 42%

• Reduce DSS events by 37%

• Reduce camera-based fatigue alarms alarms by 50%

• Reduce LTIs by 13%

Readi is a privacy-first platform, designed to provide insights regarding on-duty fatigue, while keeping private the data that goes into the model. All personal data concerning sleep, demographics, and survey responses remain private by default.