Sepal AI develops Reinforcement Learning (RL) environments and executes complex human data projects for advanced science and economically valuable tasks. The company provides a platform and operational process for creating outcome-verifiable tasks and sourcing expert networks for data projects. They also offer proprietary internal reasoning benchmarks used by leading AI labs to evaluate frontier models.
Funding
$500K raised to dateRaised to date based on public sources. This may differ from the amount the company actually raised and is based only on what is publicly available on the internet.
Founders
Product
Problem
Many organizations struggle to find high-quality, domain-specific data for training and evaluating AI models, especially in specialized fields like biology, law, and medicine. Generic datasets often lack the necessary depth and accuracy, leading to suboptimal AI performance and unreliable results.
Solution
Sepal AI provides custom data development services, including expert annotations and evaluations, to enhance the performance of AI models in specialized domains. The company leverages a network of over 20,000 PhDs and industry specialists to create high-quality datasets tailored to specific client needs. Sepal AI offers services such as custom evaluations, human baselining, and advanced AI training data, including Reinforcement Learning from Human Feedback (RLHF) and Supervised Fine-Tuning. By providing access to vetted experts and managed quality assurance, Sepal AI helps organizations build better models with reliable and accurate data.
Target Audience
Sepal AI's primary customers are organizations developing AI models in specialized domains such as biology, law, and medicine, as well as other science and professional service areas.
Features
- Custom dataset creation tailored to specific AI applications
- Expert annotations from a network of over 20,000 PhDs and industry specialists
- Custom evaluations and human baselining for AI model performance assessment
- Advanced AI training data, including RLHF and Supervised Fine-Tuning
- Dedicated operations and campaign management for data development projects
- Quality management and incentive mechanisms to ensure data reliability
- Access to experts across multiple specializations, including biology, legal, medical, chemistry, mathematics, and engineering