Model Governance, Risk & Compliance (GRC) refers to solutions that enable organizations to manage the lifecycle, oversight, and regulatory compliance of artificial intelligence and machine learning models. These platforms provide frameworks for documenting model development, assessing risks, monitoring performance, and ensuring adherence to internal policies as well as external regulations. The focus is on establishing transparency, accountability, and control over the use of models in production environments. Core capabilities include model inventory management, risk assessment, validation workflows, audit trails, and compliance reporting. Technical features often support version control, bias detection, explainability, and integration with broader enterprise GRC or risk management systems. These solutions help organizations identify and mitigate risks associated with model drift, data privacy, and regulatory non-compliance. Model GRC tools are primarily used by data science teams, risk managers, compliance officers, and IT governance professionals. Their purpose is to ensure that models operate within defined risk tolerances and meet legal or ethical standards. This category is distinct from general GRC platforms, which address broader organizational risks, and from model monitoring tools, which focus solely on performance metrics without comprehensive governance or compliance oversight. Cyberin provides a platform for discovering and comparing Model Governance, Risk & Compliance solutions to support informed decision-making.