Sepal AI

What is Sepal AI?

Sepal AI operates as a specialized data development platform that bridges the gap between AI model builders and domain experts. The platform maintains a network of over 20,000 professionals spanning STEM fields and professional services—including academic PhDs, medical professionals, finance consultants, and business analysts. Through this expert ecosystem, Sepal enables enterprises to develop high-quality, domain-specific datasets that address the limitations of contaminated public benchmarks. The platform integrates data generation tooling, synthetic data augmentation, human expertise, and rigorous quality control processes to support responsible AI development and deployment.

Key Features

• Curated Expert Network

  Access to 20,000+ verified professionals across STEM and professional services, including faculty, post-docs, and industry veterans from leading research institutions.

• Integrated Data Development Platform

  Unified environment combining data generation tools, synthetic augmentation capabilities, and quality control workflows for efficient dataset production.

• Domain-Specific Dataset Creation

  Custom benchmarks, evaluations, and training data tailored to specialized fields such as finance, healthcare, biology, physics, and professional services.

• Flexible Remote Engagement

  Gig-based participation model allowing experts to contribute on their own schedule with competitive hourly compensation ranging from $38-$104 per hour.

• Rapid Onboarding Process

  Streamlined vetting system with automated identity verification, alignment consultations, and secure access granted within days of profile creation.

Use Cases

• Model Safety Assessment : AI labs can leverage domain experts to design rigorous evaluation frameworks that test model capabilities, safety guardrails, and edge-case performance.
• Enterprise AI Deployment : Organizations building industry-specific AI applications can access specialized training data that reflects real-world complexity and domain nuance.
• Research Data Collection : Academic and commercial research teams can conduct studies with qualified professionals to gather expert-validated datasets for frontier AI development.
• Benchmark Development : AI developers can create custom, contamination-free benchmarks that accurately measure model performance in specific domains or use cases.
• Expert Knowledge Monetization : PhD holders, researchers, and industry specialists can earn additional income by contributing their expertise to cutting-edge AI projects on a flexible schedule.

FAQs