Deployments

Gradient Deployments helps you perform effortless model serving.

Easily deploy your machine learning model as an API endpoint in a few simple steps. Stop worrying about Kubernetes, Docker, and framework headaches.

Gradient makes model inference simple and scalable.

move from R&D into production with Deployments.

01

Select Model

Select an existing model or upload a new model from the interface or CLI.

02

Choose Runtime

Choose from your preferred runtime eg TensorFlow Serving, Flask, etc.

03

Serve Model

Set instance, types, autoscaling behavior, and other parameters. Click deploy!

Perfect for ML developers. A powerful no-fuss environment with loads of features that "just works."

Free signup
Easy setup
End to End

Start in seconds

Go from signup to training a model in seconds. Leverage pre-configured templates & sample projects.

Infrastructure abstraction

Job scheduling, resource provisioning, cluster management, and more without ever managing servers.

Scale instantly

Scale up training with a full range of GPU options with no runtime limits.

Full reproducibility

Automatic versioning, tagging, and life-cycle management. Develop models and compare performance over time.

Collaboration

Say goodbye to black-boxes. Gradient provides a unified platform designed for your entire team.

Insights

Improve visibility into team performance. Invite collaborators or leverage public projects.

And much more...

  • Framework agnostic
  • Model repo
  • System metrics
  • Versioning
  • Autoscaling
  • Run anywhere
  • Low-cost GPUs
  • Log streaming
  • Python CLI & SDK

Run on any ML framework. Choose from wide selection of pre-configured templates or bring your own.

Gradient Deployments are in private beta. Complete the form to join the waitlist.

Add speed and simplicity to your workflow today