New to Machine Learning? Check out learn.spell.run
Spell is a powerful platform for building and managing machine learning projects. Spell takes care of infrastructure, making machine learning projects easier to start, faster to get results, more organized and safer than managing infrastructure on your own.
Intuitive tools and simple commands allow you to quickly get started and immediately see the productivity benefits of having infinite computing capacity at your fingertips.
Explore your data with Jupyter notebooks, train models on powerful GPUs, create APIs, and automate your entire workflow, Spell makes setting up ML pipelines easy.
Run your experiments and models on your own AWS or Google cloud instance, automatically generate records, and keep your data in one place.
Empowering organizations to make better use of data and build intelligent systems, Spell allows teams to experiment faster, increases collaboration and provides full project transparency.Request DemoLearn More
Run your experiments on the cloud with GPU-enabled Jupyter Notebooks and powerful CPU and GPU machines. Spell is the easiest way to add unlimited capacity to your dev environment.View Features
End-to-end tools that make your team more productive and get faster results.
Automatic Model Serving
Turn any model into a REST API with a single command, and manage performance and scaling in our web dashboard.
End to End Workflow
Automate, monitor, and optimize the different stages of your machine learning pipeline.
Get easy performance wins with our one-command hyperparameter search.
Collaborative Jupyter Workspaces
Use Jupyter Notebooks or Jupyter Labs powered by Spell's GPUs, and easily collaborate on a notebook within an organization.
View queued and running jobs across your organization and better allocate capacity to meet your organization’s unique needs.
Deploy in Your Own Cloud
Spell’s cluster management interface allows you to manage your own cloud and spin up and down instances as needed.
I had the opportunity to work with Spell on a challenge for Omdena to preprocessing our datasets. This was a great experience because on my laptop this process took many hours while on Spell it was much faster and my laptop didn't freeze. Additionally, Spell had logs where I can monitor my process, kill the run if it is necessary, and I can see how long the run is so I can monitor performance in my code.
“Spell Unveils New, Collaborative Deep Learning and AI Development Platform, Following $15 Million Raise.”view article
Connect with our team to learn how Spell can accelerate your business.Contact Us