xpresso Version Control

Get Visibility Into Four Quadrants Of AI/ML Applications – Code, Datasets, Workflow And Models

Easy to use version control tools that helps arrive at optimum results with the ability to time-travel to previous versions as needed

Data Version Control

  • Store and version all types of data and metadata (structured or unstructured)
  • Bring together datasets from multiple sources into a repository
  • Pull datasets in your workflows directly using libraries, APIs or pre-built components

Code Version Control

  • Integrated with code repositories such as GitLab, Bitbucket and interactive notebooks such as JupyterHub
  • Keep track of all changes and bridge communication between teams
  • Leverage the language agnostic capabilities to use multiple programming languages within your solution
  • Store dependencies along with the code

Experiment & Model Version Control

  • Seamless model tracking and model versioning with a central repository to store and visualize every experiment and model along with datasets and parameters
  • Version models and rollback to previous experimentation and results when needed
  • Compare experiments and deploy the most optimum model that suits the business needs
  • Easily reproduce and transfer models into any environment

See xpresso.ai’s Version Control In Action

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