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

Build with all your tools for analytics and AI in SageMaker Unified Studio

Amazon SageMaker Unified Studio provides an integrated experience to use all your data and tools for analytics and AI. Discover your data and put it to work using familiar AWS tools for model development, generative AI, data processing, and SQL analytics. Work across compute resources using unified notebooks, discover and query diverse data sources with a built-in SQL editor, train and deploy AI models at scale, and rapidly build custom generative AI applications. Create and securely share analytics and AI artifacts such as data, models, and generative AI applications to bring data products to market faster.

Develop and scale AI with a comprehensive set of AI capabilities

Accelerate AI in SageMaker with a comprehensive set of AI development capabilities that are secure by design. Train, customize, and deploy ML and foundation models (FMs) on a highly performant and cost-effective infrastructure. Use purpose-built tools spanning the entire AI lifecycle— from high-performance integrated development environments (IDEs) and distributed training to inference, AI ops, governance, and observability. Rapidly create generative AI applications tailored to your business with cutting-edge models and your proprietary data. Speed up AI development with Amazon Q Developer, helping you more easily discover data, build and train ML models, generate SQL queries, and create and run data pipeline jobs, all through natural language.

Reduce data silos and unify all your data with SageMaker Lakehouse

Unify all your data across Amazon Simple Storage Service (Amazon S3) data lakes and Amazon Redshift data warehouses with Amazon SageMaker Lakehouse. Gain the flexibility to access and query your data with all Apache Iceberg–compatible tools and engines on a single copy of analytics data. Secure your data by defining fine-grained permissions, applied across your analytics and AI tools in the lakehouse. Bring data from operational databases and applications into your lakehouse in near real time through zero-ETL integrations. Additionally, access and query data in place with federated query capabilities across third-party data sources.

Meet your enterprise security needs with end-to-end data and AI governance

Ensure enterprise security with built-in governance throughout the entire data and AI lifecycle. SageMaker empowers you to control access to the right data, models, and development artifacts by the right user for the right purpose. Consistently define and enforce access policies using a single permission model with fine-grained access controls with Amazon SageMaker Catalog. Safeguard and protect your AI models with data classification, toxicity detection, guardrails, and responsible AI policies. Gain trust throughout your organization through data-quality monitoring and automation, sensitive data detection, and data and ML lineage.