Coretex is a powerful MLOps platform designed to make AI experimentation fast and efficient. With Coretex, data scientists, ML engineers, and less experienced users can easily:
Check the highlight video bellow to see it in action:
Coretex.ai helps you iterate faster and with more confidence. You get reproducibility, scalability, transparency, and cost-effectiveness.
VS Code extension
Coretex VS Code extension automates working with Coretex CLI and streamlines development workflow to make your iterations faster.
Among others, there are the benefits of using the extension:
Please check the list of supported commands by opening your VS Code command box [Cmd + Shift + P] and start typing "Coretex: ...".
Step 1: Sign up for a free account ->
Step 2: Install coretex:
Step 3: Migrate your project to coretex:
Read the documentation and learn how you can migrate your project to the Coretex platform -> Migrate your project to Coretex
Coretex offers a range of features to support users in their AI experimentation, including:
One of the key benefits of Coretex is its ability to guarantee reproducibility. The platform keeps track of all experiment configurations and parameters between runs, ensuring that users never lose track of their work.
Supported Use Cases
Coretex is a versatile platform that can be used for a variety of use cases, including:
Compatibility with other libraries
Coretex is compatible with all ML libraries such as Wandb, Tensorboard, PyTorch, and etc. There are no limits when it comes to Coretex integration with other libraries.
If you require any assistance or have any questions, our support team is available to help. Please feel free to reach out to us through our contact page or via email email@example.com. We will be happy to assist you with any inquiries or issues you may have. Check out the Coretex platform overview at coretex.ai for more information, tutorials, and documentation.