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Powering data-centric
AI development

Your one-stop data labeling platform. Fast data iterations and easy scaling
to support AI/ML development.

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Real value to drive your AI

Get data insights fast — at a fraction of the cost.

  • Fastest Time-to-Result

    Reduce time to labeled data from days to minutes with the largest global crowd available 24/7.

  • High Quality

    Place your confidence in state-of-the-art technologies for superb data accuracy at scale.

  • True Scalability

    Unlock scalability with versatile features, a highload system, and easy integration into ML pipelines.

  • Cost-efficiency

    Pay as you go and stay under budget with significant cost savings at scale and no data minimums.

Versatile use cases

Pre-set data labeling pipelines for a wide variety of use cases and diverse data types, with no data minimums.

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Unleash the potential of AI

Designed by engineers for engineers, Toloka supports data-related processes across the entire machine learning lifecycle — from data labeling to model monitoring.
  • Self-service data labeling platform with access to a global crowd to prepare human-labeled training data for machine learning models
  • Enterprise-level data labeling solutions, automated pre-labeling, custom datasets, and other services on request
  • Flexible data collection and data annotation tools that adapt to any use case, including computer vision, object detection with bounding boxes, natural language processing, semantic segmentation, image and text classification, video data, and collecting raw data
  • Adaptive ML models, model hosting and deployment, and model evaluation and maintenance with human-in-the-loop workflows

How Toloka’s diverse and global crowd gives you better training data

The machine learning world is realizing the need for data collected from the widest possible demographic. Otherwise, AI learns to mimic the biases of a narrow group of people.

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Featured news

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Article
Creating Responsible AI Products Using Human Oversight

To enjoy responsible AI products, we need to possess responsible models and processes. With that in mind, human oversight at every stage is crucial if we’re to make the human-machine collaboration work in our favor. While automation can be freeing, we can only build, operate, and maintain responsible AI models when key decisions are left in our hands.

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July 25, 2022

Article
Training Data: The Overlooked Problem of Modern AI

With other components of AI equally available for all the players on the market, it is data that really makes your AI solution stand out from the competition. ... those who can set up regular processes of validating and updating their solutions based on real-life data get a more reliable solution.

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June 27, 2022

Article
Why businesses take a month or more to deploy ML models and what you can do

If you’re short on time and require high accuracy, consider taking the custom adaptive route; otherwise, any custom solution can potentially fulfill your needs just as well. In terms of the overall cost, the generic route is the cheapest of all – followed by the custom adaptive route that bypasses most MLops expenses – and finally by all other custom solutions...

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June 20, 2022

Article
UNESCO-backed IRCAI names Northeastern’s and UNAM’s Civic AI Research - in collaboration with Toloka - as Most Impactful

“AI For Good: Framework to Empower Digital Workers” project, in collaboration with Toloka, was named the most impactful on the IRCAI Global Top 100 - a list of the top 100 AI projects helping to solve problems related to the United Nations’ 17 sustainable development goals (SDGs).

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Mar 18, 2022

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