Companies that use Amazon SageMaker Pipelines
It is the first purpose-built, easy-to-use continuous integration and continuous delivery (CI/CD) service for machine learning (ML). With SageMaker Pipelines, you can create, automate, and manage end-to-end ML workflows at scale.
189
companies
List of companies using Amazon SageMaker Pipelines
curl --request POST \
--url "https://api.theirstack.com/v1/companies/search" \
--header "Accept: application/json" \
--header "Content-Type: application/json" \
--header "Authorization: Bearer <api_key>" \
-d "{
\"company_technology_slug_or\": [
\"amazon-sagemaker-pipelines\"
]
}"Technology
is any of
Amazon SageMaker Pipelines
Employees26kRevenue$1.5BIT Services and IT ConsultingAmazon SageMaker PipelinesMedium confidence
Employees15kRevenue$1BBusiness Consulting and ServicesAmazon SageMaker PipelinesMedium confidence
Employees42kRevenue$26BBiotechnology ResearchAmazon SageMaker PipelinesMedium confidence
Employees777Software DevelopmentAmazon SageMaker PipelinesMedium confidence
Employees942Revenue$19MIT Services and IT ConsultingAmazon SageMaker PipelinesMedium confidence
Employees220IT Services and IT ConsultingAmazon SageMaker PipelinesMedium confidence
Employees433Business Consulting and ServicesAmazon SageMaker PipelinesMedium confidence
Employees606Revenue$33MSoftware DevelopmentAmazon SageMaker PipelinesMedium confidence
Employees5.5kManufacturingAmazon SageMaker PipelinesMedium confidence
Employees1kSoftware DevelopmentAmazon SageMaker PipelinesMedium confidence
We have data on 189 companies and users that use Amazon SageMaker Pipelines. Our Amazon SageMaker Pipelines users and customers list is available for download and comes enriched with vital company specifics, including industry classification, organizational size, geographical location, funding rounds, and revenue figures, among others.
Technology Usage Statistics and Market Share
How to target Amazon SageMaker Pipelines users
- How to customize this list?
You can customize this data to your needs by filtering for geography, industry, company size, revenue, technology usage, job postions and more. You can download the data in Excel or CSV format.
- How to be alerted when companies adopt this technology?
You can get alerts for this data. You can get started by selecting the technology you are interested in and then you will receive alerts in your inbox when there are new companies using that technology.
- How to import this data to my CRM?
You can export this data to an Excel file, which can be imported into your CRM. You can also export the data to an API.
Frequently asked questions
Our data is sourced from job postings collected from millions of companies. We monitor these postings on company websites, job boards, and other recruitment platforms. Analyzing job postings provides a reliable method to understand the technologies companies are employing, including their use of internal tools.
We refresh our data daily to ensure you are accessing the most current information available. This frequent updating process guarantees that our insights and intelligence reflect the latest developments and trends within the industry.
Amazon SageMaker Pipelines is a sophisticated technology within the realm of Machine Learning Tools, designed to streamline the process of building, managing, and deploying machine learning workflows. It enables data scientists and developers to create end-to-end ML pipelines that are efficient, scalable, and easy to reproduce. By providing a visual interface for building workflows, Amazon SageMaker Pipelines simplifies the complexity of managing ML tasks, allowing users to focus more on the development and optimization of models.
Amazon SageMaker Pipelines falls under the category of Machine Learning Tools, specifically focusing on pipeline orchestration and automation. This technology helps in structuring ML workflows by defining each step from data preparation to model deployment, ensuring a cohesive and efficient process. It allows for versioning of each step, facilitating reproducibility and collaboration among team members working on ML projects. With features like automated retraining and model monitoring, Amazon SageMaker Pipelines enhances the efficiency of machine learning development cycles.
Founded by Amazon Web Services, Amazon SageMaker Pipelines originated from the growing need to simplify and streamline the machine learning workflow process for data scientists and developers. Launched as part of the Amazon SageMaker ecosystem, the technology aimed to address the challenges faced in managing complex ML pipelines and enable faster experimentation and deployment of models. Since its inception, Amazon SageMaker Pipelines has gained significant traction in the market, establishing itself as a prominent player in the Machine Learning Tools category.
In terms of current market share, Amazon SageMaker Pipelines holds a strong position within the Machine Learning Tools category. With the increasing adoption of machine learning technologies across various industries, the demand for robust pipeline orchestration tools like Amazon SageMaker Pipelines is expected to grow further. Industry forecasts suggest a positive outlook for the technology, indicating a potential increase in market share as organizations continue to invest in optimizing their machine learning workflows.