AI Model Evaluation, Red Teaming & Assurance refers to solutions and services designed to assess, test, and validate the security, robustness, and reliability of artificial intelligence and machine learning models. This category focuses on identifying vulnerabilities, adversarial risks, and compliance gaps within AI systems, ensuring that models perform as intended under both normal and hostile conditions. Core capabilities include adversarial testing, model auditing, threat simulation, and performance benchmarking. These solutions often employ techniques such as red teaming, penetration testing, and automated evaluation to uncover weaknesses in model architecture, data pipelines, and deployment environments. They may also provide assurance frameworks for regulatory compliance and risk management specific to AI-driven applications. Typical users include security teams, data scientists, machine learning engineers, and compliance officers in organizations deploying AI models in sensitive or high-stakes contexts. The primary objective is to proactively identify and mitigate risks unique to AI systems, which differ from traditional software vulnerabilities. This category is distinct from general application security or vulnerability management, as it addresses the specific challenges posed by machine learning algorithms, data integrity, and adversarial manipulation. Cyberin offers a platform for discovering and comparing AI Model Evaluation, Red Teaming & Assurance solutions.