SAGA by AIceberg fulfills requirements for AI governance, risk, compliance, and quality assurance, while addressing security and efficiency. It provides deep insight into how AI models make decisions, making 'black box' AI systems more interpretable and explainable. SAGA combines initial in-depth and ongoing real-time analysis for data drift, model drift, and potential security compromises, ensuring reliability and security for the complete AI life cycle. It analyzes any classification or regression model without the need to integrate code and avoids vendor lock-in. SAGA enables full data and model analysis at least 50 times faster than traditional methods like LIME or SHAP for faster and more efficient AI development and deployment. Counterfactual analysis and simulation capabilities help understand model behavior in hypothetical or past scenarios, essential for AI development and risk management. SAGA analyzes the entire training dataset and processes synthetic data through the AI model for deeper insights into performance and behavior. It seamlessly integrates insights and simulations into existing workflows via API. SAGA solves the communication gap between data science teams and stakeholders with reports for both technical and non-technical teams. It maps controls to regulatory frameworks and assesses compliance, critical for organizations in regulated industries. SAGA manages risks associated with third-party AI models as organizations rely more on external AI services and tools. It is an independent and auditable system of record for safe and compliant AI use. SAGA processes large datasets, provides insights, and supports monitoring for predictive tools across various markets, including Financial Services, Healthcare, Human Resources, and E-commerce.
