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Instant infrastructure for Machine Learning

Train your model in the cloud instantly.
Deploy in 1-click.




We are the GPU lambda functions for ML

Wide ML library support

Full support for PyTorch, TensorFlow2.0 and MXNet. Also 🤗.

Immediate access to GPUs

We always connect your ML task to the fastest range of top-tier GPUs, from T4 to V100s and more.

Scale as you go

From 1 to 100s servers. Our infrastructure will scale with your needs.

Only pay for compute time

From researchers to enterprise grade, we got a plan for you!

Serverless means

more time focusing on building ML

optimise your compute expense

flexible infrastructure

Serverless means

more time focusing on building ML

optimise your compute expense

flexible infrastructure

How it works

Focus on building models, not infrastructure.

Compile your model

Build your model with your ML library of choice and upload the model with the API.

Tensorflow 2.0 / Pytorch / MXNet
Easy prototyping
Easy deployment

Train or Predict

Train with your model or run predictions, for research or production, from a python script or from your notebook of choice.


Done. Let the API do magic

We know what is the best GPU resource for your model and task. Our ML powered infrastructure will train or run inference on the fastest GPU.

From prototype to production

Train and Deploy your ML in a few lines


Train your Model

Train in parallel

Track any metric

Automatic visualisations

Get Started

Deploy your Model

1 line predictions

Scale as you go

JSON support

Get Started

Frequently Asked Questions

Where does my datasets and models go when uploaded via the API?

All your data is stored in AWS S3 servers.

Can I choose what GPU you use?

Part of our offering is that you don't have to worry about what GPU to use. Our infrastructure selects the fastest GPU for your application. If you want a specific GPUs, you can contact us for our enterprise plan.

Can I use your API inside Jupyter Notebook?

Yes, you can use the API from anywhere.

THE API for serverless ML compute

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