# Aws Amazon Sagemaker

> Publicly sourced profile assembled by Optimly, in the Optimly AI Brand Index. Last refreshed 2026-10-04.

- **Business Profile:** https://optimly.ai/brand/aws-amazon-sagemaker
- **Dataset:** https://optimly.ai/brand/aws-amazon-sagemaker.json
- **Markdown:** https://optimly.ai/brand/aws-amazon-sagemaker/llms.txt
- **Official website:** https://amazon.com
- **Slug:** aws-amazon-sagemaker
- **Categories:** ai-machine-learning, data-analytics-business-intelligence

## Overview

- **Tagline:** Provides an integrated experience for analytics and AI with unified access to all data, comprehensive ML development capabilities (including FMs and generative AI), built-in governance, and accelerated development with Amazon Q Developer, all within a fully managed, serverless studio.
Source: Brand's website (https://amazon.com) · 2026-10-04

- **Description:** Amazon SageMaker is an integrated experience for analytics and AI, bringing together widely adopted AWS machine learning and analytics capabilities. It enables users to build, train, and deploy ML models (including foundation models), unify data access across various sources, and govern data and AI assets within a single development environment.
Source: Brand's website (https://amazon.com) · 2026-10-04

## Offerings

- **Core capabilities:**
  - Amazon SageMaker AI (for ML model development
  - training
  - deployment
  - MLOps
  - generative AI)
  - Amazon SageMaker Unified Studio (integrated development environment for analytics and AI)
  - Amazon SageMaker Catalog (data and AI governance)
  - SageMaker Lakehouse (unified data access and lakehouse architecture).
Source: Brand's website (https://amazon.com) · 2026-10-04

- **Pricing:** Not explicitly detailed on the page, but typical for AWS services, likely a pay-as-you-go, usage-based model.
Source: Brand's website (https://amazon.com) · 2026-10-04

## Audience

- **Target industry:** Enterprises, startups, data scientists, ML engineers, developers, and analysts across various industries who need to build, train, and deploy AI/ML models, perform data analytics, and manage data and AI governance at scale.
Source: Brand's website (https://amazon.com) · 2026-10-04

Page last updated 2026-10-17.