Introducing: Cortex Pipeline Management
Today, Vidora released Pipeline Management within Cortex, our self-service Machine Learning platform. As enterprise organizations increasingly deploy Cortex across their businesses, it’s important that they be able to organize and track thousands of distinct ML initiatives across disparate teams. Pipeline Management provides a simple interface which enables Cortex newcomers to quickly build and manage ML models, while also providing flexibility to scale their Cortex usage to thousands of unique models.
Simplify Your Pipeline Building Experience
Fortune 500 companies rely on Cortex to enable Machine Learning within their businesses. Pipeline Management makes it easier for disparate teams to collaborate and manage large number of models built within Cortex. This allows our partners to scale their ML efforts across every part of the organization.
Pipeline Management provides the flexibility to organize various ML pipelines in ways that make sense for any business. Our partners use Cortex to bring ML capabilities to multiple teams within their organizations – Marketing, Product, Operations, etc. Now, through an intuitive system of tagging and sorting, you can create distinct workspaces to track changes, compare performance, and export results across the pipelines that matter to you.
Vidora’s partners are building more and more models within Cortex, and their feedback pointed to a need for tools to manage those models. “We wanted to build a solution for our partners which could scale to meet both their current and future needs,” said Neven Wang-Tomic, the lead Vidora engineer on the project. “Pipeline Management minimizes the overhead involved in accessing your ML pipelines, ensuring that the right stakeholders across your business have access to the right pipelines within Cortex.”
Organize your Models to scale your ML initiatives across teams.
Learn More About Cortex
Interested in seeing a demo or learning more? Let us know by emailing email@example.com!