From Google Cloud Storage to ML modeling in Minutes

Connect your Google Cloud Storage to cnvrg.io and enable rapid ML development with preconfigured ETL, permissions, versioning and configurations

Flexible

Use any language, AI framework, and compute environment. Integrate and
version any kind of data to reuse in any project, experiment, and/or notebook

Interactive

Use any development environment like JupyterLab, RStudio, and more with pre-installed dependencies and version control

Unified

One unified environment to manage, build and deploy your machine learning with all your favorite data science tools

Learn more about the Google Cloud Storage integration

Google Cloud Storage is a RESTful online file storage web service for storing and accessing data on Google Cloud Platform infrastructure. The service combines the performance and scalability of Google’s cloud with advanced security and sharing capabilities.

Google Cloud Storage Documentation →

Instantly build machine learning models

Instantly train models on your data using the AI library of advanced ML components
Choose from dozens of ready made preprocessing scripts and training algorithms
Set up an end-to-end, production-ready, ML pipeline in minutes with your own data

Data Access Layer

Manage all your team’s data sources in one centralized location
Easily change between data sources with simple CLI or UI connectivity
Control datasets with advanced access permission levels both by user and by compute

Data Version Control

Automatically version data of any size and with the ability to
associate models to specific versions
Create metadata for each object to track, manage and store labels