Toloka

Toloka AI BV supplies expertly curated data for developing AI agents and models, combining human experts with machine learning technology. Its offerings span agent training and evaluation data, coding data, LLM and VLM datasets, creative AI data, evaluation and AI safety red-teaming. A self-serve platform, labeled version 2 and beta on the site, lets users describe a data goal and have an agent build the collection and annotation pipeline.

What It Is

Toloka is a training-data and human-evaluation provider for AI developers. The company says it enhances the skills and safety of frontier and specialized models, covering agentic skills, AI safety, coding skills, text generation and reasoning, and image, video and audio generation. Services include demonstration generation for supervised fine-tuning, preference collection for RLHF/DPO, auto-verifiable tasks for evaluation and RL training, and customized human evaluation and red teaming.

Data for Agents and Models

For agent development, Toloka describes environment generation (simulated environments for training and evaluating agents), specialized training datasets for agentic skills, and evaluation and red-teaming. Listed agent types include conversational agents, corporate assistants, deep research agents, computer use agents, coding copilots and OS agents. Agent data offerings include trajectory demonstrations, virtual environments and RL-gyms with MCP replicas, and safety red-teaming for injection vulnerabilities.

How the Self-Serve Platform Works

Users describe their project, data type and use case, optionally attaching reference files, and answer clarifying questions about pipeline structure, workforce split, consent flows and regional storage. The agent builds a multi-stage pipeline whose nodes (data structure, task UI, quality criteria, guidelines, pricing, QA method) can be reviewed before deployment. Users calibrate quality by completing a few tasks, then experts label while an LLM QA system validates every output; human QA is also available. Validated results are then downloaded. Task types include RLHF and preference data, data collection, instruction tuning, model evaluation, synthetic data validation and content moderation QA.

Experts and Quality Control

Work is matched to domain experts, general annotators or a global crowd. The site states 90+ domains of expertise and contributors from 100+ countries, and describes quality control with golden sets, dynamic overlaps, cross-validation and built-in post-verification. Toloka states it is ISO 27001 and ISO 27701 certified and SOC 2, GDPR, CCPA and HIPAA compliant, with Microsoft Azure as base infrastructure.