Toloka Looking To Scale Up Recruitment In India/South East Asia

Yandex’s Toloka has announced plans to expand its crowdsourced talent base of Tolokers by tapping India’s billion-strong worker base. The company also seeks to make inroads into countries in the surrounding region.

Toloka is a cloud-based platform, which generates machine learning data at scale by harnessing the wisdom of the crowd from around the world. It operates a crowdsourced model that lets any individual in any country log on, complete tasks, and earn extra income in their spare time.

To ensure impeccable quality standards, Toloka has implemented a number of quality control measures such as smart matching of performers to tasks, AI-based predictions of task performance quality, and flexible review settings with options for both automated and manual task acceptance.

India is a world leader in STEM education, producing over 2 million qualified graduates each year, and English is widely spoken. Toloka now plans to focus on seeking out task performers in this region to leverage its talented, tech-literate population.

Olga Megorskaya, Toloka CEO, said:

We’re excited to continue our push into India, as well as into the surrounding areas, including Pakistan, Myanmar, Bangladesh, and Indonesia. Our 300,000 Tolokers from this region have already proven extremely valuable to our customers, but a great deal of untapped potential remains in this market. We hope to see new talents from India and beyond on our platform soon, and look forward to setting new industry standards together.

In addition to Toloka’s unparalleled focus on the quality of its work, the company is also working to improve industry-wide standards. Toloka professionals have recently begun teaching the world’s first free course on crowdsourced data-labeling, launched by Yandex on Coursera, to educate the next generation of people interested in working with data.

Source: Yandex Press Release

Header Image: Toloka used and adapted with permissions from Toloka, via press agency.

Dan Taylor
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