Security and Governance for AI Models

In today’s rapidly evolving digital landscape, AI and ML models have become integral to organizational operations, but they also introduce significant risks. Our Model Risk Management system serves as a frontline defense against adversarial AI threats, focusing on robustness, fairness, and explainability evaluations.

We developed a comprehensive solution with a battery of attacks to test ML models for robustness, explainability, and fairness. Utilizing FastAPI endpoints, data scientists can expose adversarial attack simulations, fairness evaluations, and model explainability analyses, facilitating seamless integration into existing systems. Models and datasets are securely stored in an AWS S3 bucket in .joblib format for streamlined data storage and retrieval. PyCharm and Dockerdash were employed for coding FastAPI endpoints and containerizing the code, respectively, enhancing portability and ease of management.

The solution serves as a valuable tool for validating model risks, ensuring the security and reliability of the AI ecosystem. In an era where AI’s role in business operations is pivotal, our Model Risk Management service offers a robust approach to AI security, enabling organizations to harness AI’s power while safeguarding against potential threats. As the AI landscape evolves, our system remains a reliable partner, ensuring enterprise AI/ML models remain secure, compliant, and resilient in the face of adversarial challenges.