South Korean food delivery platform Baemin discloses results of AI scheduling system KAIROS: severe delivery delays cut by 50%
Baemin operator Woowa Brothers disclosed that its AI platform KAIROS shifted from headcount to 'supply time' prediction, cutting severe delivery delays by 50% and operational response time by 90%.
Woowa Brothers, the operator of South Korean food delivery platform Baemin, disclosed the operational results of its AI-based rider supply automation platform 'KAIROS' at the Woowa Tech Conference 2026 held in Seoul on October 28. According to data scientist Shin Sung-chan and data analyst Ju Ga-ram, KAIROS automates the entire process from rider supply prediction and target selection to operational response.
Traditional scheduling systems typically compare the number of riders needed for expected orders with the number of riders predicted to actually work. However, because each rider's operating time varies, it is difficult to accurately assess actual delivery processing capacity based solely on headcount. To address this, KAIROS changed its prediction basis from 'number of riders' to 'supply time'. The system utilizes approximately 20 machine learning models to analyze order demand, required operating time, and each rider's expected operating duration, considering the probability of riders responding to requests and their expected duration to select personnel.
This shift resulted in significant improvements in operational efficiency. According to Woowa Brothers, KAIROS reduced dispatch time by 25% and decreased excessively delayed deliveries by 50%. Additionally, to cope with sudden weather changes and order surges, the system shortened its prediction cycle from once daily to every 10 minutes, forecasting supply and demand conditions for the next 30 minutes to one hour. This led to a 20% reduction in regions deviating from quality standards, a 74% decrease in the duration of quality deterioration, and a 90% reduction in the operational team's response time.