Spell

The MLOps platform for running, managing, and scaling machine learning.

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Overview

Spell is an MLOps platform that provides the infrastructure and tools for machine learning teams to run, manage, and scale their workflows. It offers features for experiment tracking, resource management, model deployment, and collaboration. Spell is designed to be easy to use and to integrate with existing ML tools and workflows.

✨ Key Features

  • Experiment Execution and Tracking
  • Resource Management and Orchestration
  • Model Deployment and Serving
  • Collaboration and Project Management
  • Cloud-agnostic
  • Jupyter Notebook Integration

🎯 Key Differentiators

  • Simplicity and ease of use
  • Focus on providing a seamless infrastructure experience for ML
  • Cloud-agnostic approach

Unique Value: Spell provides a simple and powerful platform for running, managing, and scaling machine learning, allowing teams to focus on building models instead of managing infrastructure.

🎯 Use Cases (4)

Running and tracking machine learning experiments Managing and scaling compute resources for ML Deploying models to production Collaborating on ML projects

✅ Best For

  • Used by companies to manage their machine learning infrastructure and streamline their MLOps workflows.

💡 Check With Vendor

Verify these considerations match your specific requirements:

  • Individuals or small teams with minimal infrastructure needs.

🏆 Alternatives

Valohai Determined AI Polyaxon Domino Data Lab

Compared to more complex platforms, Spell offers a more streamlined and user-friendly experience for managing ML infrastructure.

💻 Platforms

Web API CLI

🔌 Integrations

AWS GCP Azure Kubernetes Docker TensorFlow PyTorch Jupyter

🛟 Support Options

  • ✓ Email Support
  • ✓ Live Chat
  • ✓ Phone Support
  • ✓ Dedicated Support (Contact Sales tier)

🔒 Compliance & Security

✓ SOC 2 ✓ GDPR ✓ SSO ✓ SOC 2 Type II

💰 Pricing

Contact for pricing

✓ 14-day free trial

Free tier: NA

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