Build, train, and deploy ML models with Amazon SageMaker AI (formerly Amazon SageMaker)

Amazon SageMaker

The next generation of Amazon SageMaker is the center for all your data, analytics, and AI

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Overview

Bringing together widely adopted AWS machine learning (ML) and analytics capabilities, Amazon SageMaker delivers an integrated experience for analytics and AI with unified access to all your data. Collaborate and build faster from a unified studio using familiar AWS tools for model development, generative AI, data processing, and SQL analytics, accelerated by Amazon Q Developer, the most capable generative AI assistant for software development. Access all your data whether it’s stored in data lakes, data warehouses, or third-party or federated data sources, with governance built in to meet enterprise security needs.

Benefits

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Customers

Toyota

"To address siloed data sets spread across our automotive operations, we are implementing Amazon SageMaker to help unify and govern data across our connected car, sales, manufacturing, and supply chain units. This approach allows us to search, discover, and share data effortlessly, laying the groundwork to pre-empt quality issues, increase customer satisfaction, and enable easier development of generative AI applications."

Kamal Distell, VP of Data, Analytics, Platforms, and Data Science, TMNA

Charter Communications

Charter Communications is driving innovation and efficiency with Amazon Redshift and Amazon SageMaker.

Lennar

"We have spent the last 18 months working with AWS to transform our data foundation to use best-in-class solutions that are cost effective as well. With advancements like Amazon SageMaker Unified Studio and Amazon SageMaker Lakehouse, we are accelerating our velocity of delivery through seamless access to data and services, thus enabling our engineers, analysts, and scientists to surface insights that provide material value to our business."

Lee Slezak, SVP of Data and Analytic, Lennar

Natera, Inc

"Our organization has been leveraging Amazon DataZone, Amazon SageMaker AI, Amazon Athena, and Amazon Redshift to manage and analyze our clinical and genomic data. We are excited to now have the unified governance of the Amazon SageMaker Catalog, which will streamline our data discovery and access, enabling our team to quickly analyze relevant data across our whole domain. This integration will help us create tailored datasets, potentially reducing our time-to-insight, and ultimately drive improved patient outcomes as we advance our goal of making personalized genetic testing a standard part of care."

Mirko Buholzer, VP of Software Engineering, Natera, Inc.

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NatWest Group

"Our Data Platform Engineering team has been deploying multiple end-user tools for data engineering, ML, SQL, and gen AI tasks. As we look to simplify processes across the bank, we’ve been looking at streamlining user authentication and data access authorization. Amazon SageMaker delivers a ready-made user experience to help us deploy one single environment across the organization, reducing the time required for our data users to access new tools by around 50%."

Zachery Anderson, CDAO, NatWest Group

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