I will investigate the contemporary ecosystem of workplace algorithmic surveillance deployed by Yandex, a data platform based in Russia which combines the data infrastructure of Google and the working conditions of Uber. Yandex dominates Russian logistical networks through its multiple products, which all draw from its database - taxi, food delivery, maps and algorithmic solutions for business logistics. After attaining a virtual monopoly in ride-hailing with its purchase of the Russian branch of Uber in 2017, and far surpassing Google in its Russian search market, Yandex was able to create an enormous logistical network and solutions for its surveillance. The logistical infrastructures of Yandex cannot be disentangled from algorithmic surveillance - a key technology for governing labour that operates extensively in contemporary logistical industries. Yandex profits from the absence of a functional governmental policy on privacy protection. Its monopoly enables total workplace surveillance, creating "poverty and stress" among employees with the new ways of control "when there should be wealth and leisure", as Tiziana Terranova notes in the context of other platform economies. Yandex workers manifest "poverty and stress"  in their exhaustion, starvation, death due to overwork, and overall impossibility of unionisation. Yandex’s algorithms heavily underestimate the time workers need to cover their assigned distances, making it impossible for them to rest or to comply with the delivery requirements, resulting in heavy cuts from their wages.