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SAIF CHECK's team of experts specialize in AI risk assessment throughout the AI product lifecycle,  to ensure accuracy, reliability, efficiency & transparency.​  Our team uses:

  • Industry best practices

  • Up-to-date international compliance regulations

  • Cutting-edge AI technologies


    • To help you identify potential issues & optimize your AI system's performance.


    • Ensure the accuracy of your AI models through our comprehensive assessment with actionable insights for improvement​.


    • To help you streamline your AI system, reducing operational costs & improving overall efficiency.



Dr. Shaista Hussain is a Clinical Pathologist, Machine Learning Engineer and Medical Researcher. She has a deep passion for developing cutting-edge algorithms and machine learning models, with years of experience in explainable, responsible & ethical AI. Dr. Shaista also has extensive experience in Data Analysis; Blockchain & Cryptocurrency, CRISPR Cas9 Genomics, as well as in application development.  Dr. Hussain is an influential thought leader and accomplished researcher having published numerous scientific papers and has spoken at prestigious conferences worldwide.

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Norah Alsubaie brings a unique blend of expertise in human behaviour management and project leadership to the forefront of AI safety and compliance. With a foundation in understanding complex behavioural patterns, Norah expertly navigates the intricacies of AI technology, ensuring products are developed with ethical considerations and user safety in mind. Her adeptness in translating behavioural insights into operational excellence fuels SAIF CHECK’s mission to deliver trustworthy AI solutions. Norah’s leadership embodies a commitment to integrating human-centric principles in the advancement of safe AI technologies.

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Milan McGraw stands as a preeminent senior executive, epitomising leadership and innovation within the realms of Artificial Intelligence, Machine Learning, and Generative AI. At the helm of AI/ML Generative AI Services for Amazon Web Services (AWS) with a focus on Financial Services and Capital Markets, McGraw wields an unparalleled expertise, steering the development and implementation of cutting-edge AI solutions and championing the principles of responsible AI.  Milan is esteemed for his contributions to academia and professional development. As the Lead Machine Learning Instructor at, an initiative led by the renowned Andrew Ng, and serving as an Adjunct Professor at both Northwestern University and the City Colleges of Chicago, he dedicates himself to unravelling intricate problems through AI, data science, and system design. McGraw’s professional narrative before AWS is marked by a series of influential leadership positions, from Deep Learning Engineer and Head of Data Science to Chief AI Strategist at EX3 Labs, a prominent Digital Strategy Firm. His stewardship was critical across various sectors, including retail, consumer packaged goods, and financial services. His comprehensive expertise spans a vast array of AI disciplines such as generative AI, machine learning, LLMOps/MLOps, and responsible AI, equipping him with the insight to tackle and navigate complex challenges within these domains. McGraw’s illustrious career is further distinguished by a commendable 9-year service as a US Marine Platoon Commander, underscoring his exemplary leadership qualities and unwavering commitment to excellence. Milan McGraw’s journey is a beacon of innovation, strategic leadership, and transformative impact in the fast-evolving landscape of AI and technology.

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Garima Choudhary is currently pursuing a specialisation in AI and ML as a Computer Science student, and is a highly accomplished data scientist with a proven track record of success in the field. With a strong background in machine learning and data analysis, Garima has consistently delivered impactful insights to drive strategic decision-making. She has spearheaded several high-profile projects rooted in classifications and explainable AI, and recently completed the Taiwan Experience Education Program (TEEP), where she expanded her expertise in diverse AI applications and cross-cultural collaboration. Additionally, Garima has been recognized for her outstanding contributions to the industry, receiving the Data Science Excellence Award for her innovative work in anomaly detection algorithms. Garima's academic and professional experiences reflect a deep dedication to leveraging technology for social good, positioning her as a promising innovator in the AI community.

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Juan Olano is a  Systems and Computer Engineer and a seasoned entrepreneur with over three decades of experience. Juan brings a deep expertise in software development and a pioneering spirit in AI technology, particularly in the development of Tiny Models. Juan's work focuses on creating micro transformer-based models that are both efficient and scalable, optimized for deployment on consumer-grade devices. This innovative approach not only democratizes AI by making it accessible and affordable but also aligns with his commitment to delivering cutting-edge solutions that are both powerful and sustainable.  Juan has also led the development of systems spanning Recommender Systems and Computer Vision, grounded in robust practices in MLOps and API-based development.

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Wallace Ferreira is a distinguished Research Scientist and Engineering Professor with a wealth of experience in data science and multidisciplinary optimization. With a Ph.D. focusing on implementing algorithms for engineering problems, Wallace has led impactful projects in AI/ML-based software development, showcasing his expertise in business intelligence and engineering simulation. Drawing from professional engineering experience in the automotive industry, Wallace has utilized numerical methods and data-driven optimization for product development, ensuring efficiency and innovation.  Beyond consultancy, Wallace’s background includes teaching at prestigious engineering faculties and active participation in international open-source projects as a volunteer data scientist. His commitment to knowledge sharing is evident through his involvement in technical and scientific conferences as a lecturer and reviewer, along with publications in renowned journals, solidifying his reputation as a valuable asset in the data science and machine learning landscape.

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