Case study

Governed AI sandbox for financial services

Usecase

Banks need a secure and compliant way to experiment with generative AI and machine learning while meeting strict regulatory and data governance requirements. Traditional experimentation environments often introduce risk, lack oversight, or make it difficult to transition successful pilots into production.

This use case provides a governed AI sandbox built on AWS, leveraging NVIDIA AI technologies and services such as Amazon SageMaker. It enables teams to experiment with AI using synthetic or anonymised data in the cloud, while maintaining strong controls over access, security, and auditability.

By combining secure cloud-based experimentation with a clear path to on-premises or production deployment, banks can accelerate innovation, build internal AI capability, and move confidently from proof of concept to operational use.

Key Features

  • Secure AI experimentation environment on AWS
  • Support for NVIDIA AI software and accelerated compute
  • Use of Amazon SageMaker for managed model development and testing
  • Enforced governance, access control, and audit logging by design
  • Safe use of synthetic or anonymised data for experimentation
  • Clear transition from cloud-based experimentation to production environments

Future Expansion

The sandbox can evolve into an AI operations capability, supporting model lifecycle management, monitoring, and ongoing governance as AI use cases scale across the organisation.

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