In TrustTest there are specialized components designed to assess if an AI model response is compliant with a specific set of criteria. They provide a systematic way to measure various aspects of model outputs against predefined criteria, ensuring reliable and consistent evaluation across different use cases.
Quality Assurance
Evaluators provide objective metrics to ensure AI responses meet quality standards and requirements.
Consistent Assessment
By standardizing evaluation criteria, evaluators enable reproducible and comparable results across different models and use cases.
Flexible Evaluation
The modular design allows for custom evaluators to be created for specific needs while maintaining a consistent interface.
Comprehensive Analysis
Different types of evaluators can be combined to provide a holistic assessment of model performance across multiple dimensions.
Trust and Reliability
Systematic evaluation helps build confidence in AI systems by providing clear metrics and explanations for assessment results.