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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.
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.
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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.
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.
The Indian Institute of Hotel Management (IIHM) specializes in hospitality education that offers high-quality training and effective placement solutions. Based in India, the institute worked with AWS PartnerWorkmates to implement an AWS generative AI solution based on Amazon Bedrock. As a result, IIHM is seeing 50 percent faster interviews, 90 percent hiring accuracy, and a 20–30 percent higher rate of student job placements. In addition, surveys show that IIHM has created a more engaging learning environment, with 75 percent of educators and students now feeling more secure interacting with AI-generated content.
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.
Learn the 7 critical AWS services and architectural patterns solutions architects need for implementing enterprise-scale AI solutions. From optimizing performance to ensuring security, this comprehensive guide equips you with the knowledge to build robust, scalable AI-driven architectures with AWS.
Export for vCenter is a new AWS Open Source Python project you can use to export vCenter inventory data for import into AWS Transform for VMware. Export for vCenter retrieves only the data required as inputs for AWS Transform for VMware and AWS Transform Assessments. The data is exported into CSVs with columns matching the [...]
Durga Sury, Raj Bagwe, Sri Aakash Mandavilli, Edward Sun,
07/10/2025
AI developers and machine learning (ML) engineers can now use the capabilities of Amazon SageMaker Studio directly from their local Visual Studio Code (VS Code). With this capability, you can use your customized local VS Code setup, including AI-assisted development tools, custom extensions, and debugging tools while accessing compute resources and your data in SageMaker Studio. In this post, we show you how to remotely connect your local VS Code to SageMaker Studio development environments to use your customized development environment while accessing Amazon SageMaker AI compute resources.
Sarah Aamir, Michael Hilmen, Cedric Hu,
07/14/2025
While cloud adoption accelerates, many industries still rely on legacy systems for critical workloads. This blog explores how Solace’s PubSub+ facilitates cloud migrations using the Strangler Fig pattern and a data-first approach. PubSub+ enables seamless, real-time data movement across hybrid environments, helping enterprises modernize without disrupting business continuity. Learn how this IDC-recognized event-driven solution addresses key migration challenges.
Dimitrios Spiliopoulos, Gabriel Verreault, Gary Emmerton,
07/11/2025
In today’s competitive industrial landscape, providers of industrial machines, such as construction and mining equipment, and factory machinery, look for innovative ways to maximize the potential of their products. By connecting these machines to the cloud with IoT, machine builders gain visibility into how their equipment performs in real-world conditions—understanding utilization patterns, identifying recurring failure [...]