Amazon SageMaker, an integrated experience for data, analytics, and AI, enables customers to work with their data, whether for analytics or AI, help them get to AI-ready data faster, and improve productivity of all data and AI workers.
SageMaker brings together AWS ML and analytics capabilities and provides unified tools for model development, generative AI, data processing, and SQL analytics, along with built-in generative AI powered by Amazon Q Developer that guides you along the way of your data and AI journey.
SageMaker Lakehouse unifies all your data across Amazon Simple Storage Service (Amazon S3) data lakes and Amazon Redshift data warehouses, helping you build powerful analytics and AI/ML applications on a single copy of data.
SageMaker Catalog simplifies the discovery, governance, and collaboration for data and AI across your lakehouse, AI models, and applications.
Amazon SageMaker Unified Studio (Preview) provides an integrated authoring experience to use all your data and tools for analytics and AI. All your favorite functionality and tools are now available in one place, helping you discover and prepare data with ease, author queries or code, and get to insights faster.
Moving forward, we’ll refer to this set of AI/ML capabilities as SageMaker AI, and we’ll continue to innovate and expand on them.
SageMaker still includes all the existing ML and AI capabilities for data wrangling, human-in-the-loop data labeling with Amazon SageMaker Ground Truth, experiments, MLOps, Amazon SageMaker HyperPod managed distributed training, and more.
SageMaker also comes with built-in generative AI powered by Amazon Q Developer that guides you along the way of your data and AI journey, transforming complex tasks into intuitive conversations.
The next generation of SageMaker delivers an integrated experience to access, govern, and act on all your data by bringing together widely adopted AWS data, analytics, and AI capabilities.
Innovate faster with the convergence of data, analytics and AI.