LEVAL provides a secure platform for evaluating AI models, offering unbiased and fair ratings based on proprietary datasets and standardized criteria. This helps businesses and institutions confidently adopt AI by providing clear, actionable insights into model performance without data leakage risks.
Funding
Funding not disclosed
Founders
Product
Problem
Organizations face challenges in objectively evaluating AI models due to biased methodologies, data contamination, and the risk of data leakage. Existing benchmarks often reuse training data or are known to model providers, leading to inaccurate and unreliable performance assessments. This lack of trust hinders confident AI adoption and exposes businesses to potential risks.
Solution
Leval provides a secure and independent platform for evaluating AI models, offering unbiased ratings based on proprietary datasets and standardized criteria. The platform uses private, unreleased datasets to prevent data contamination and ensure genuine evaluation. Leval's methodology focuses on fairness, transparency, and scientific rigor, starting with benchmarks like Leval-S, which measures gender bias in model outputs. By providing clear, actionable metrics and transparent processes, Leval empowers organizations to make confident AI decisions and navigate AI risks effectively.
Target Audience
The primary audience includes research labs, enterprises, and policymakers seeking fair, transparent, and secure AI model evaluations.
Features
- Secure AI model evaluation with zero risk of data leakage or model contamination
- Customizable evaluation criteria tailored to specific use cases
- Proprietary datasets to guarantee independence from public benchmarks
- Transparent processes and reproducible methodology
- Leval-S benchmark for evaluating gender bias and stereotyping in model outputs
- Leaderboard showcasing model performance across various benchmarks
- Standardized evaluation settings, including controlled temperature and sampling parameters