Streamline Machine Learning from Experimentation to Production
A standardized end-to-end MLOps pipeline that tracks your ML projects from model experimentation to production deployment.
Intuitive web dashboard with all logs, request metrics and machine metrics.
Supports standard machine learning libraries like Tensorflow and Pytorch out of the box, easy to customize with additional dependencies.
Deploy to Production with One Command
Kubernetes cluster management to save you time enabling model serving and autoscaling.
Easily deploy models that you've trained on Spell or uploaded to the platform.
Easy deployment with high performance load balancing and state of the art async web server.
Model Management and Versioning
Full transparency with end-to-end lineage tracking that shows where and how your model was trained.
An intuitive versioning feature that allows for faster experimentation of your models.
Promote team collaboration by keeping model training details and notes all in one place.
Machine Learning Projects with Spell
Request a Demo
Schedule a personalized demonstration with a Spell representative to learn how Spell can help streamline and accelerate your machine learning development.
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.