List of Amazon SageMaker AI Infrastructure Customers
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Since 2010, our global team of researchers has been studying Amazon SageMaker AI Infrastructure customers around the world, aggregating massive amounts of data points that form the basis of our forecast assumptions and perhaps the rise and fall of certain vendors and their products on a quarterly basis.
Each quarter our research team identifies companies that have purchased Amazon SageMaker AI Infrastructure for AI infrastructure from public (Press Releases, Customer References, Testimonials, Case Studies and Success Stories) and proprietary sources, including the customer size, industry, location, implementation status, partner involvement, LOB Key Stakeholders and related IT decision-makers contact details.
Companies using Amazon SageMaker AI Infrastructure for AI infrastructure include: Adobe, a United States based Professional Services organisation with 31360 employees and revenues of $23.77 billion, GE HealthCare, a United States based Healthcare organisation with 53000 employees and revenues of $19.60 billion, Intuit, a United States based Professional Services organisation with 18200 employees and revenues of $18.83 billion, Zendesk, a United States based Professional Services organisation with 5000 employees and revenues of $2.33 billion and many others.
Contact us if you need a completed and verified list of companies using Amazon SageMaker AI Infrastructure, including the breakdown by industry (21 Verticals), Geography (Region, Country, State, City), Company Size (Revenue, Employees, Asset) and related IT Decision Makers, Key Stakeholders, business and technology executives responsible for the software purchases.
The Amazon SageMaker AI Infrastructure customer wins are being incorporated in our Enterprise Applications Buyer Insight and Technographics Customer Database which has over 100 data fields that detail company usage of software systems and their digital transformation initiatives. Apps Run The World wants to become your No. 1 technographic data source!
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| Logo | Customer | Industry | Empl. | Revenue | Country | Vendor | Application | Category | When | SI | Insight |
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Adobe | Professional Services | 31360 | $23.8B | United States | Amazon Web Services (AWS) | Amazon SageMaker AI Infrastructure | AI infrastructure | 2025 | n/a |
In 2025, Adobe deployed Amazon SageMaker AI Infrastructure to scale generative model lifecycle capabilities, Category: . The implementation anchors model training, tuning, and endpoint hosting for AI agents and inference workflows that support Adobe’s creative and marketing product portfolio.
Amazon SageMaker AI Infrastructure was configured to manage training pipelines, model registries, and hosted endpoints alongside orchestration for agent deployment. Implementation focused on standard AI infrastructure modules including distributed training orchestration, hyperparameter tuning, model versioning, and managed inference endpoints, enabling repeatable model development and continuous delivery of models into application workflows.
The deployment interoperates with AWS compute and storage documented in the collaboration, with training workloads running on Amazon EC2 P5 and P6 instances and datasets persisted in Amazon S3 and FSx for Lustre. SageMaker-hosted models feed into Adobe product AI surfaces described in the joint announcement, while other AWS services referenced across the stack include Amazon Bedrock and emerging agent primitives such as Amazon Bedrock AgentCore for multi-agent capabilities.
Operational coverage spans Adobe’s flagship creative and marketing functions, integrating with Adobe Express conversational editing, Acrobat Studio AI assistants, Firefly generative workflows, and Adobe Experience Platform driven applications like Real-Time CDP, Journey Optimizer, and Customer Journey Analytics. Governance emphasizes centralized data and model workflows on AWS, aligning AEP-driven profile and audience constructs with SageMaker model endpoints to support content supply chain automation, CX orchestration, and performance marketing activation.
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GE HealthCare | Healthcare | 53000 | $19.6B | United States | Amazon Web Services (AWS) | Amazon SageMaker AI Infrastructure | AI infrastructure | 2018 | n/a |
In 2018, GE HealthCare deployed Amazon SageMaker AI Infrastructure as the AI Infrastructure underpinning its GE Health Cloud in the United States. GE HealthCare runs GE Health Cloud on Amazon Web Services and uses Amazon SageMaker AI Infrastructure to build, train, and deploy machine learning models for medical imaging and analytics, supporting clinical collaboration and patient outcomes.
The implementation centralized storage for imaging datasets and established scalable ML workflows that handle data ingestion, model training, and model deployment pipelines. Amazon SageMaker AI Infrastructure is used to operationalize deep learning development for imaging analytics, with functional emphasis on model training orchestration, deployment endpoints, and iterative model retraining workflows.
Architecturally the deployment is hosted on AWS and integrated directly into GE Health Cloud storage and data pipelines for imaging data, enabling end to end model lifecycle management within the cloud environment. The configuration emphasizes scalable compute for training and inference, centralized dataset management for medical imaging, and orchestration of model artifacts to downstream clinical analytics services.
Governance and operational scope focused on embedding SageMaker as the planned platform for deep learning functionality across GE Health Cloud services in the United States. The move enabled centralized storage and scalable ML workflows for imaging data and positioned Amazon SageMaker AI Infrastructure as the foundational AI Infrastructure for future imaging and analytics capabilities.
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Intuit | Professional Services | 18200 | $18.8B | United States | Amazon Web Services (AWS) | Amazon SageMaker AI Infrastructure | AI infrastructure | 2022 | n/a |
In 2022, Intuit implemented Amazon SageMaker AI Infrastructure to modernize its AI and machine learning platform supporting finance and tax products in the United States, under the AI Infrastructure category. The Amazon SageMaker AI Infrastructure deployment was paired with other AWS AI services such as Bedrock to accelerate model development and deployment lifecycles. The scope centered on accelerating experiments, production model rollout, and MLOps for finance and tax product teams.
Implementation concentrated on building model development and deployment pipelines, managed training and inference environments, a model registry and monitoring, and experimentation workflows to support continuous delivery of models. Amazon SageMaker AI Infrastructure was configured to host automated training jobs, orchestrated deployment pipelines, and runtime monitoring, enabling data scientists to shift effort from infrastructure management to product features. Integrations explicitly included AWS Bedrock alongside SageMaker services to support foundation model use cases and model orchestration.
Governance emphasized operational MLOps practices, model lifecycle governance, and runtime observability to align model releases with finance and tax product release processes across Intuit in the United States. The modernization tripled Intuit's speed to delivery and freed data scientists to focus on product features and customer outcomes.
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Professional Services | 5000 | $2.3B | United States | Amazon Web Services (AWS) | Amazon SageMaker AI Infrastructure | AI infrastructure | 2023 | n/a |
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