Companies that use Kedro
It is an open-source Python framework for creating reproducible, maintainable and modular data science code. It borrows concepts from software engineering best-practice and applies them to machine-learning code; applied concepts include modularity, separation of concerns and versioning.
475
companies
List of companies using Kedro
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\": [
\"kedro\"
]
}"Technology
is any of
Kedro

Employees46kRevenue$13BBusiness Consulting and Services
KedroHigh confidenceEmployees11Software Development
KedroHigh confidence
Employees251Software Development
KedroHigh confidence
Employees50IT Services and IT Consulting
KedroHigh confidence
Employees35Software Development
KedroHigh confidence
Employees2.2kInsurance
KedroHigh confidence
Employees9Technology, Information and Internet
KedroHigh confidence
Employees41Biotechnology
KedroHigh confidence
Employees204Education
KedroHigh confidence
Employees375Revenue$25MInsurance
KedroHigh confidence
We have data on 475 companies and users that use Kedro. Our Kedro 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 Kedro 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.
Kedro is an open-source Python framework designed to facilitate the development of robust data pipelines. It offers a high level of flexibility and scalability, making it ideal for managing complex workflows in data science and machine learning projects. By providing a standardized approach to structuring code and data, Kedro enables teams to collaborate effectively and maintain a clear understanding of the pipeline's architecture.
In the realm of Frameworks (Full Stack), Kedro falls under the category of data pipeline frameworks. It focuses on streamlining the process of building, deploying, and managing data pipelines that are crucial for extracting insights from large datasets. Kedro's emphasis on modularity and reproducibility sets it apart, allowing users to easily experiment with different data processing techniques and iterate on their pipelines with confidence.
Kedro was founded in 2019 by QuantumBlack, a data science consultancy that aimed to address the challenges faced by data professionals in structuring and managing their projects effectively. Drawing on their extensive experience in the field, QuantumBlack developed Kedro to provide a comprehensive solution for building scalable and maintainable data pipelines. Since its inception, Kedro has gained traction among data engineering and data science teams looking to streamline their workflow and enhance collaboration.
In terms of current market share, Kedro has been steadily gaining popularity within the data engineering and data science communities. Its user-friendly interface, extensive documentation, and active community support have contributed to its growing adoption rate. As organizations continue to recognize the importance of efficient data pipeline management, Kedro is poised to experience further growth in the foreseeable future, cementing its position as a leading framework in the data science ecosystem.