Scale AI vs Toloka

Scale AI and Toloka are both platforms for creating, annotating and assessing the quality of data for training AI models. They support various data types (text, images, audio, video) and use a human-in-the-loop model, meaning some of the work is performed by humans, while the platforms connect the clients (AI developers) and the performers (annotators).

But Scale AI (founded in 2016) is an American Meta-backed company that initially focused on data annotation for autonomous vehicles and computer vision. It also operates subsidiary platforms Remotasks (for universal data annotation) and Outlier (for high-level tasks related to LLM). It works with major AI labs and corporations (Google, Microsoft, OpenAI, Meta) and places a strong emphasis on data security.

Toloka (2014) is a European Bezos-backed company that was initially created as a microtask and crowdsourcing platform for training Yandex search algorithms. Over time, the company shifted its focus: not only on labeling but also on creating custom datasets, dialogues, complex tasks for teaching LLM. The platform not only works with regular performers but also engages experts for highly specialized tasks (medicine, finance, law, etc.). Toloka uses cross-validation methods, "golden tasks" and dynamic overlay to ensure high data quality.