Case Study: a Fortune 500 bank achieves secure, compliant MLOps at scale with Shakudo

How a top U.S. bank scaled secure, compliant enterprise AI fast with Shakudo's OS for AI and data—cutting costs and accelerating MLOps

The customer, a Fortune 500 bank, faced significant challenges in scaling its secure and compliant machine learning operations. With a team of over 100 AI practitioners, the bank’s existing MLOps stack, heavily reliant on SageMaker, was fragmented and lacked integration, observability, and cost transparency, hindering its ability to innovate within a regulated financial environment. They turned to vendor Shakudo for a solution.

Shakudo implemented its operating system for AI and data, migrating the bank's models from SageMaker to its platform. The solution provided secure, compliant deployment within the bank's own infrastructure, deep cost observability, and robust model monitoring. This enabled the bank to improve efficiency for its AI teams, deploy workloads that met stringent financial regulations, and implement batch processing with full cost transparency at scale.