Our approach includes ongoing assessments that monitor the performance and behavior of LLMs for maintaining the integrity and utility of AI models long-term.
Sapien employs a hybrid red teaming method that blends automated attack simulations with expert human insights to detect potential severe vulnerabilities and undesirable behaviors.
We are preparing to introduce certifications that attest to the safety and capability of AI applications according to the latest standards. This service will provide our clients with a credible assurance of their AI solutions' reliability and safety.
Preventing AI from generating false or nonexistent information
Addressing the spread of incorrect or misleading information
Mitigating the risks of advice on critical topics which could cause harm
Eliminating biases that perpetuate stereotypes and cause harm to specific groups
Safeguarding against the disclosure of personal information
Protecting AI systems from being exploited in cyberattacks
Our team consists of highly skilled professionals in security, technical domains, national defense, and creative fields, all equipped to undertake sophisticated evaluations. With expertise drawn from multiple distinct domains, Sapien’s red teamers are qualified to scrutinize and improve the safety of your AI models.
At Sapien, we believe that human insight is invaluable in fine-tuning AI models. Our data labeling services are designed to provide high-quality training data that reflects real-world complexities and nuances, enabling AI applications to perform with high accuracy and adaptability.
Discover how Sapien can assist in building a scalable and secure data pipeline for your AI models with testing and evaluation services.