Toloka AI BV
Toloka empowers businesses with high-quality data to develop AI products that are safe, responsible and trustworthy. It combines human expertise, machine-learning technology and quality assurance to produce training, alignment and evaluation data for AI agents and models.
At a Glance
- Frontier AI labs and foundation-model developers
- Big-tech and Fortune 500 companies
- AI startups and enterprise AI teams
- Robotics and physical-AI developers
- +2 more
AI Tools by Toloka AI BV
(2)Toloka
AI Training Data and Evaluation
Tendem
AI Tasks With Human Experts
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Latest News
Nebius and Toloka announce integration to bring human experts on demand to AI agents through Tendem MCP.
Tendem introduced as a hybrid AI agent combining AI orchestration and vetted human expertise.
Bezos Expeditions led a $72 million investment in Toloka, with participation from Mikhail Parakhin.
Forbes coverage examined virtual testing environments and enterprise AI-agent adoption, highlighting the market Toloka serves.
Products & Services
AI-assisted platform that turns a plain-language data goal into a complete collection and annotation pipeline, including task design, expert matching, automated LLM QA, human QA and downloadable results.
Managed services for supervised fine-tuning demonstrations, RLHF/DPO preference data, auto-verifiable evaluation and RL-training tasks, customized human evaluation and red teaming across text, image, audio and video.
Hybrid AI agent for professionals, small teams and entrepreneurs. It decomposes complex work, delegates subtasks to AI and vetted human experts, and applies automated and human verification; use cases include research, writing, analysis and content creation.
Model Context Protocol integration that makes vetted human expertise callable inside AI-agent workflows and is being integrated into the Nebius ecosystem.
Market Position
Toloka positions itself as an expert-led, human-in-the-loop alternative to commodity data-labeling vendors and AI-only evaluation tools. Its differentiation is the combination of a global expert network, managed operations, automated/LLM quality assurance and specialized generative-AI data; relevant competitors include Scale AI, Appen, Surge AI and Labelbox.
Leadership
Founders
Olga Megorskaya
Founder and CEO; has more than a decade of experience in AI and data labeling and extensive experience managing distributed technical and non-technical teams.
Executive Team
Olga Megorskaya
Founder and CEO
Founded Toloka in 2014; has more than a decade of AI and data-labeling experience and also serves as CEO of Mindrift.ai.
Board of Directors
Founding Story
Toloka began in 2014 as a crowdsourcing and microtasking platform for data markup intended to improve machine-learning and search algorithms. As AI models became more capable and the required work more complex, the company evolved from mass-market labeling toward expert-driven, human-AI collaboration for generative-AI training, alignment and evaluation.
Business Model
Revenue Model
B2B managed AI-data services and a self-service platform. Customers pay for completed data-collection, annotation, training-data and evaluation work; the platform says pricing is calculated after project setup and customers pay only for work that passes QA.
Pricing Tiers
No hidden fees, minimums or contracts; credit-card payment is supported through Stripe, and customers pay for work that passes QA.
For customers preferring data services managed by Toloka's team.
Target Markets
- Frontier AI labs and foundation-model developers
- Big-tech and Fortune 500 companies
- AI startups and enterprise AI teams
- Robotics and physical-AI developers
- Companies building coding, reasoning, multimodal and creative AI
- Organizations requiring AI safety, evaluation or red teaming
- Training and fine-tuning large language models and generative-AI systems
- AI-agent skill and tool-use data
- Model evaluation and benchmarking
- RLHF and preference optimization
- Coding, text/reasoning, image/video/audio and multimodal model development
- AI safety, red teaming and content-moderation QA
- Anthropic
- Amazon
- Microsoft
- poolside