Powering data-centric
AI development

A unified environment to support fast and scalable AI/ML development:
from data collection and annotation to model training, deployment and monitoring.

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Maximize the value
of your AI

Accelerate experiments
with fast data iterations
Scale your projects
with high-performance tools
and unlimited crowd power
Tune your models
with whatever new data
you need, when you need it
Integrate
with end-to-end
ML pipelines

Covering the entire ML lifecycle

The Toloka environment allows data scientists
and ML teams to get AI solutions to production faster by:

Testing hypotheses
Boosting the success rate of prototypes
Building optimal data production pipelines that can be integrated into the ML production cycle

Data collection
Data processing
Store, process and clean data
Data annotation
Data analysis
Model training, deployment,
and evaluation
Model monitoring

Our products and open source libraries

Data labeling and collection platform

Our platform is purpose-built for scaling and acceleration to meet any data labeling demands.

Support for any type of data and task
On-demand access to our diverse global crowd
Flexible annotation tools: use our templates or design your own with code and no-code interface editors

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Adaptive AutoML

New

Our collection of pre-trained models are ready to use out of the box and adapt to fit your data.

Pre-trained on large datasets with human verification for high accuracy
Continuous optimization and retraining using your data streams for reliable performance
Available via API with low latency for model predictions

Try out models

ML platform

New

Our ML platform is engineered for comparing datasets, tracking experiments, calculating metrics, and tuning models.

Versioning for models and datasets
Visualizations, reports and diffs
Python API for access from any environment

Explore ML platform

Powerful open API

Our open source libraries for Python and Java provide API access to all the features of the Toloka data labeling platform.

Toloka-Kit is a Python library for working with Toloka via API. It allows you to build scalable and fully automated human-in-the-loop ML pipelines and integrate them into your processes.
Toloka-Java-SDK allows working with API functionality using JVM-based languages.

Tools for labeled data

Crowd-Kit is an open source Python library that simplifies working with crowdsourced data.

Aggregation methods for categorical, pairwise, textual, and segmentation responses
Metrics for evaluating uncertainty, consistency, and agreement with aggregate
Loaders for popular crowdsourced datasets

Pipeline management

Integrate your data labeling processes with popular workflow management platforms using our open-source Python libraries.

Build automated data processing workflows using ready-made tasks for frequent actions.

Apache Airflow integrationPrefect integration

Designed by engineers for engineers
to scale AI development

Toloka supports a community of data scientists, ML engineers, researchers,
and AI innovators around the globe to accelerate machine learning with better data processes

Trusted by leading ML&AI teams
"With Toloka we were able to resolve even the most difficult cases of recognizing handwritten text in documents for our customers."
Founder and CTO of Dbrain, Y Combinator alum
"Toloka is our source for a continual stream of data for large-scale projects. We collected the world's largest database of 200,000 unique photos and videos."
Science Director and Co-founder
"Thanks to Toloka, we're able to run numerous data projects on a regular basis. What we gain is a dependable approach to data labeling."
Crowd Solutions Architect
"Toloka is the first place we go to prepare data for Al. We get a full set of quality control tools and it's 10 times cheaper than our previous solution."
Head of Technologies
"We were really impressed with how fast we got our project done in Toloka - 10,000 ads were reviewed in just 12 hours."
Special Projects Team
“We use Toloka to prepare training data for speech technologies. It allows us to quickly test different markup methods and hypotheses and then choose the optimal approach.”
Data scientist

Why Toloka

State-of-the-art technologies
Advanced tools and unique approaches
backed by 10+ years of industry
experience and research
- Crowd management tools and quality
  control options
- Flexible foundation models pre-trained
  on large datasets
- Automated processes combining
  human insights and machine learning
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Global crowd
Millions of Tolokers across every time zone for on-demand labeling, instant scaling, and multilingual projects
- 40+ languages, 100+ countries
- 200k+ monthly active Tolokers
- 800+ daily active projects
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Robust secure infrastructure
Fault-tolerant high-load system for rapid
knowledge enrichment that prioritizes
data security and privacy
- GDPR-compliant, ISO 27001-certified
- Automatic scaling to handle any volumes
- Secure data storage options
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