AWS Machine Learning Competency Partners

Drive innovation and unlock greater business value with AWS Specialization Partners that have deep technical knowledge and proven customer success

AWS Machine Learning Competency Partners have demonstrated expertise delivering machine learning (ML) solutions on the AWS Cloud. These partners offer a range of services and technologies to help you create intelligent solutions for your business, from enabling data science workflows to enhancing applications with machine intelligence.

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Data processing such as ingestion, consolidation, removal of duplicate records, imputation of missing values, scaling/normalization of values, elimination of correlated features, feature engineering, and others.

No and low-code platforms for machine learning, usually with a predominantly visual interface, that enable end-to-end model development.

High-code solutions, RESTful API, GraphQL, and algorithms that provide access to trained models and components used to train models.

AWS ML Competency Partners have demonstrated expertise in helping organizations solve the most challenging problems in AI, including data engineering, data science, machine and deep learning, and production deployment for inference at scale.

Development, deployment, and maintenance of ML applications that positively impact customer business outcomes and add value on top of AWS services, in particular AWS AI Services, to solve specific customer needs.

Continuous integration and continuous deployment solutions for ML models over the entire data lifecycle including data lake creation, automated data preprocessing across data services, deployment in the cloud, and machine-learning-specific rules and processes for model redeployment.

Connect with AWS Machine Learning Competency Partners

Drive innovation, meet business objectives, and get the most out of your AWS services by partnering with technically validated AWS Partners.

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Additional Resources

Discover more AWS Machine Learning Competency Partner solutions and resources.

  • General Resources
  • Maximizing Your Machine Learning Investment

    Explore AWS Machine Learning Competency Partner eBooks, webinars, customer success stories, and more.

    View the AWS Machine Learning Partner Resources »

    Machine Learning Foundations

    Watch the on-demand webinars and discover how these technologies are essential for digital transformations.

    View AWS Machine Learning Partner Foundations »

  • Success Stories
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    • Media & Entertainment

      Cloudar Helps Ladrokes.live Transform The Sports Fan Experience With Cloud-Native Scalability

      Belgium

      Ladbrokes.live, a provider of streaming sports entertainment content operating in Belgium, was grappling with critical challenges that hindered their ability to attract and retain users. Partnering with AWS Partner, Cloudar—also based in Belgium—the company transitioned to a cloud-native architecture powered by Amazon Web Services (AWS) technologies. This transformation enabled Ladbrokes.live to deliver a seamless, personalized user experience featuring avatars that can be customized to deliver information and statistics relevant to the viewers’ interests, in their language of choice. The solution also helped Ladbrokes.live optimize operational costs and set the stage for continuous innovation in a highly competitive industry.

      2025
    • General Public Services

      Wildlife-Centered AI: How AWS and Tehanu Use Generative AI to Give Wildlife a Voice in Global Conservation

      Rwanda

      The Tehanu project in Rwanda’s Volcanoes National Park has demonstrated groundbreaking use of generative AI to infer and act on the interests of mountain gorillas. Leveraging technology solutions from Amazon Web Services (AWS), AWS Partner Anthropic, and with the support of AWS Partner Adastra, Tehanu created an automated pipeline to process behavioral data of gorillas, enabling the first-ever digital financial transactions by a non-human species. The AI solution synthesized vast academic and observational data, aligning conservation actions with species-specific preferences while supporting biodiversity efforts. This scalable, innovative approach sets a precedent for using AI to foster coexistence across species worldwide.

      2025
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  • APN TV
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  • eBooks
  • AI Solutions for Financial Services

    Appen’s artificial intelligence (AI) experts explain how to identify and implement successful machine learning and AI initiatives.

    View the eBook »

    Machine Learning Within Reach

    Learn how to connect with Amazon SageMaker to develop, test, and deploy machine models at scale and take advantage of cost-effective, pay-as-you-go pricing.

    View the eBook »

    Weave AI Into Your Business

    Learn how to prepare for, embed, and put AI into production quickly to solve complex business problems.

    View the eBook »

    Mining Your Data Lake for Analytics Insights

    Learn about using Delta Lake on Databricks and AWS to prepare and deliver data that drives valuable analytics insights.

    View the eBook »

  • Blogs
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    • Max Peterson, 11/29/2024
      Around the world, organizations are evaluating and embracing artificial intelligence (AI) and machine learning (ML) to drive innovation and efficiency. From accelerating research and enhancing customer experiences to optimizing business processes, improving patient outcomes, and enriching public services, the transformative potential of AI is being realized across sectors. Although using emerging technologies helps drive positive [...]
    • Jonathan Jenkyn, Michael Tschannen, 02/11/2025
      March 27, 2025: Two policies in this post were updated. Generative AI applications often involve a combination of various services and features—such as Amazon Bedrock and large language models (LLMs)—to generate content and to access potentially confidential data. This combination requires strong identity and access management controls and is special in the sense that those [...]
    • Aileen Zheng, 03/12/2025
      In recent years, public sector organizations have found success running their scientific data processing workloads on Amazon Web Services. As the number of workloads increase with the massive data volume and complex scientific simulations, organizations are looking for ways to optimize cost while maintaining research momentum. Amazon EC2 Spot Instances presents a compelling option to run unused Amazon Elastic Compute Cloud (Amazon EC2) capacity with an up to 90 percent discount compared to On-Demand prices. However, the intermittent nature of Spot Instances often requires careful consideration, especially when handling time-sensitive mission-critical workloads. In this post, we discuss how organizations can effectively identify opportunities to use Spot Instances and Amazon Q Business to develop an enhanced Spot Instance analysis.
    • Luciana Decristofaro, Jon Friesen, João Bozelli, 03/28/2025
      Introduction For more than a decade, Amazon Web Services (AWS) has enabled customers to modernize their businesses. AWS provides simplified, API-based access to a range of services, including Networking, Compute, Analytics, Messaging, Security and Identity, Mobile Services and Generative AI. These services allow customers to experiment and innovate at faster pace, without requiring a heavy [...]
    • Satveer Khurpa, Andrew Kane, Antonio Rodriguez, Shyam Srinivasan, 03/28/2025
      Amazon Bedrock Guardrails announces the general availability of image content filters, enabling you to moderate both image and text content in your generative AI applications. In this post, we discuss how to get started with image content filters in Amazon Bedrock Guardrails.

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