Case Study

Leverage Machine Learning and Data Analytics

Starting Point

A financial services company was looking to transition to the AWS Cloud while prompting their data scientist community to leverage machine learning and data analytics. The client sought to enable AWS SageMaker platform to achieve several key objectives. First and foremost, they aimed to ensure secure access to data, notebooks, onboarding, and job training, prioritizing the protection of sensitive information. Additionally, the client aimed to provide the best possible experience for their data scientist community, optimizing their usage of AWS SageMaker for seamless model development, deployment, and MLOps. To facilitate cost management and resource allocation, the client sought to track chargebacks and usage effectively. It was necessary to accomplish these goals in a fashion that could easily accommodate growth and evolving business needs.

The Problem

The financial services company encountered several obstacles during their transition, primarily due to a lack of internal expertise. Concerns arose regarding the protection of sensitive information as they began establishing a secure access framework. Additionally, the client struggled to provide their data scientist community with an optimal user experience, hindering their productivity and the effective utilization of SageMaker’s platform's capabilities. The accurate tracking of chargebacks and usage proved to be another challenge, impeding the client's ability to allocate costs efficiently and identify areas for optimization. The client lacked the necessary expertise to design a robust framework capable of accommodating future growth and evolving business needs. They saw the need for external guidance to achieve their targets. The client brought in CG Infinity.

The Solution

CG Infinity proved to be an invaluable guide for the client throughout the process. CG Infinity began by reviewing the solution architecture and building the backlog and sprints during two weeks of requirements gathering, design, and planning. Afterward, the team focused on equipping the ops team and data scientists with necessary tools and documentation. CG Infinity successfully built a business process that streamlined the creation of SageMaker notebooks and secure data access for the ops team, exceeding expectations by offering solutions that leveraged AWS services. The project culminated in the client successfully testing a business use case with real data. CG Infinity's expertise and dedication proved instrumental in guiding the client towards an effective implementation and enablement of SageMaker platform.


Financial Services


Northwest, USA



Key Technology