xpresso Control Center

Centralized Management Console

Enable team collaboration with reusable components, utilities, libraries and automated tools; ensure seamless management of the development, deployment, and post-production feedback loop of data science solutions

Manage End-To-End AI Development Lifecycle

  • Create projects and workflows for data scientists and data engineers working on AI/ML projects
  • Streamline the process of creating machine learning pipelines, data processing pipelines
  • Integrate with existing applications and business processes

Leverage Best-Of-Breed Productivity Tools & Technologies

  • Facilitate team collaboration with Bitbucket, JupyterHub and Gitlab
  • Perform exploratory data analysis through Matplotlib, Seaborn, etc.
  • Support all machine learning programming languages including Python, R, etc.
  • Enable distributed computing systems like Spark, Hive and ElasticSearch

Automated MLOps With Distributed Training And DevOps Capabilities

  • Track and manage training experiments along with metrics in real time
  • Trace model lineage with data, code, model and parameters
  • Deploy model into production with automated CI/CD/CT

See xpresso.ai’s Control Center In Action

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