Sciloop

What It Does

Sciloop is a specialized platform that connects frontier AI labs with world-class domain experts to generate high-quality training data and benchmarks that push the boundaries of what AI models can solve. The platform serves as a marketplace where elite mathematicians, physicists, computer scientists, chemists, and biologists create challenging problem sets designed to test and train the most advanced AI systems.

Who It's For

Sciloop serves two primary audiences: AI research labs and enterprises building cutting-edge models who need expert-verified datasets, and elite domain experts including IMO Gold Medalists, Codeforces Grandmasters, IPhO/IChO/IBO Gold Medalists, ICPC World Finalists, Putnam Fellows, and top researchers across STEM fields who want to contribute to AI advancement while earning competitive compensation.

Key Features & Capabilities

• Expert Network: Global community of the sharpest minds across mathematics, physics, computer science, chemistry, biology, and expanding into law, economics, humanities, and medicine
• Problem Marketplace: Browse and solve open problems at your own pace with no deadlines or quotas
• Competitive Compensation: $225+ per problem for expert contributors
• Continuous Data Streams: AI labs receive continuously delivered, expert-verified datasets with real-time updates
• Quality Control: Multi-expert review process ensures data integrity and accuracy
• Custom Dataset Generation: Labs specify domain, difficulty, format, and volume requirements
• Frontier-Focused: Every dataset is built to challenge the threshold where current AI models fail

Typical Workflows

For experts: Browse active problem sets on platform.sciloop.dev, solve problems in areas of expertise, submit solutions with LaTeX support, and receive payment upon acceptance. For AI labs: Define dataset requirements, let Sciloop handle expert sourcing and quality control, receive streaming data updates, and adjust specifications as research evolves.

What Differentiates It

Sciloop distinguishes itself by focusing exclusively on frontier-level problems that current AI models cannot solve, ensuring datasets remain valuable as capabilities advance. The platform's rigorous expert vetting process (recruiting only proven top performers in international competitions and research) guarantees unprecedented data quality. The continuous streaming model allows AI labs to receive data as it's created rather than waiting for batch completion, accelerating research cycles.