Top-quality data
Collect and annotate training data that meets and exceeds industry quality standards thanks to multiple quality control methods and mechanisms available in Toloka.
Scalable projects
Have any amounts of image, text, speech, audio or video data collected and labeled for you by millions of skilled Toloka users across the globe.
Save time and money with this purpose-built platform for handling large-scale data collection and annotation projects, on demand 24/7, at your own price and within your timeframe.
Free, powerful API
Build scalable and fully automated human-in-the-loop machine learning pipelines with a powerful open API.

Data labeling for ML models

With Toloka, you can control the accuracy of data labeling to develop high performing ML models.
Data labeling
for Сomputer Vision
Our platform supports annotation for image classification, object detection and recognition, semantic segmentation, and more. Labeling tools include bounding boxes, polygons and keypoint annotation.
Data labeling
for Natural Language Processing
Our platform supports annotation for named entity recognition (NER), text classification, speech recognition, sentiment analysis, intent classification, text recognition, and more.

Crowdsourcing means unlimited resources

Data collection and labeling processes place high demands on the time, skills and expertise of a large number of people. Toloka gives you access to an unlimited crowdforce available 24/7 across the globe, plus intelligent tools and quality control methodologies for transparent and scalable workflows.

Real-time insights

Track your projects with real-time statistics on progress, spending, quality, time spent on tasks and active users involved. Leverage detailed analytics to fine-tune as necessary and make timely decisions to optimize speed, quality and budget.
Success stories
Get started now
Take advantage of Toloka technologies. 
Millions of Tolokers are available for your projects 24/7.
Start now
Contact us
Tue Sep 14 2021 18:13:28 GMT+0300 (Moscow Standard Time)