Toloka

Pick Toloka if you're building advanced AI agents that require realistic simulated environments and expert-annotated trajectories for reinforcement learning. Its strengths shine in agentic skills like tool use, browsing, and coding copilots, where step-by-step evaluation data is critical. The platform also offers safety red-teaming, which is essential for production deployments. Pass on Toloka if you only need basic text classification or image bounding boxes—simpler tools like Prodigy or Scale AI might be more cost-effective. Compared to Scale or Labelbox, Toloka emphasizes agent-specific data and human-in-the-loop expertise for complex tasks, making it a better fit for frontier AI labs. A caveat: pricing is not publicly listed, so expect a custom quote that may be steep for smaller teams. Also, while the page mentions integrations via MCP replicas, no specific third-party tools are named, so you'll need to accommodate their proprietary pipeline.

Toloka is a data solutions platform that combines human expertise and technology to build high-quality training data for AI agents and large language models (LLMs). It is designed for teams developing agentic AI systems, from conversational agents to computer-use agents, offering specialized data for training, evaluation, and red-teaming. Key features include context-rich simulated environments for agent evaluation, step-by-step trajectory demonstrations, and safety red-teaming for injection vulnerabilities. Toloka also provides domain-specific datasets for reinforcement learning, expert human evaluation, and professional annotation across text, image, video, and audio. Trusted by leading AI teams including frontier labs and big tech companies, Toloka positions itself as a premium data partner rather than a generic annotation service, offering end-to-end support for complex AI training needs.