The co-founders of NtechLab, a developer of algorithms for the recognition of faces and silhouettes, Alexander Kabakov and Artem Kukharenko left the company, lost their majority stake and left the board of directors.
This happened a few months ago, but, as CNews writes, it has only become known now. The news was confirmed to the publication by internal sources of the company and the co-founders of the project.
Alexander Kabakov stepped down from NtechLab's board of directors in December 2021. Artem Kukharenko, director of the company's neural network lab, did so a little later. His place on the board, as indicated in the Cypriot register, was taken by the head of the planning, analysis and strategy department of Alfa Capital Management Company, Alexei Panyushkin.
These events were preceded by the loss in 2021 of the NtechLab co-founders of a controlling stake in the company as a result of several investment rounds.
It is known that in 2020, the Emirati fund Mubadala and the Russian Direct Investment Fund (RDIF) became the project's investors, and in early 2018, a minority stake in NtechLab was transferred to the Ruben Vardanyan fund and the RT-Business company. . Development (a subsidiary of Rostec).
As CNews learned from a source within the company, the split may also be due to the fact that the project's founders insisted on developing international projects. And there were prerequisites for this: in 2021, NtechLab became the winner of the G20 Innovation League international competition in the AI category.
Apparently, the new investors preferred an integrated approach and intend to develop both directions at once: both domestic and foreign.
NtechLab is mainly known for its projects for recognition of faces, emotions and silhouettes of people: for example, FindFace (the platform is used by the Department of Information Technologies of the Moscow Government, law enforcement and other government agencies).
In early June, the Moscow region government also announced a test launch of the NtechLab video analytics platform that recognizes silhouettes. It will help assess the workload of more than 200 high-traffic objects and ensure their security.
Author:
Ekaterina Alipova
Source: RB

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