Amazon Web Services

The future of Machine Learning

AWS logo

We partnered with AWS on their next-generation product, SageMaker Studio—a machine learning and insights platform that is simple, powerful, and future-flexible.

AWS logo

A more accessible ML

AWS wanted to open up machine learning capabilities to more people, so we designed a no-code interface that allows users to easily build models and generate predictions, all within a collaborative environment.

To top it off, we added new dynamic infographics, resulting in a lot less intimidation and a lot more illumination.

AWS Sagemaker Studio patch panel
AWS SageMaker Canvas collaborative analytics environment

Empowering experts

We studied ML users to design workflows that empowered researchers to prepare data, collaborate on development, and deploy their models—all on a single web platform.

By combining research and heuristic evaluation, we pinpointed specific usability enhancements to ensure every step was tailored to its use case.

AWS SageMaker user archetypes
AWS SageMaker tools and features

A north star design system

SageMaker Studio required a visual language overhaul, including streamlined interactions, new dynamic patterns, and a cohesive framework. To achieve this, we created a uniquely branded, eye-popping design system called Bloom.

Accelerating teams

Our team worked closely with the AWS team, coordinating parallel tracks of work that allowed design, product management, and engineering to conceptualize, build, test, and deploy the new SageMaker faster than you can say “agglomerative clustering.”

AWS SageMaker project schedule example