Now with model registry!

Collaboration for
Machine Learning Teams

Seamless data and model management, experiment tracking, visualization and automation, with Git as the single source of truth.

Combine the power of leading open-source tools:

Our experts will help you get started and answer any questions you may have
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See how Iterative Studio can make your ML teams more productive
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7,000+
Community members
250
Open source contributors
500+
Companies
14,000+
Stars on GitHub

Built for ML researchers, practitioners, and managers

NEW

Model Registry for Machine Learning

Use your Git repositories to build a model registry with model versioning, lineage, and lifecycle management.

Enable model organization and discovery across all your ML projects. Manage model lifecycle with Git, unifying ML projects with the best DevOps practices. Use your favorite interface - GUI, CLI or API.

ML experiment tracking, visualization, and collaboration

Iterative Studio performs your ML bookkeeping automatically, to provide your team easy and efficient knowledge sharing and collaboration.

Get quick access to important metrics across multiple projects. Visualize and compare ML models. Use GitHub/GitLab/Bitbucket for ML teams, along with your own cloud and remote storage for your data and models.

Software engineering stack for ML teams

Apply proven best-practices across domains, and ensure optimum utilization of skills and resources.

Don’t reinvent the wheel. Use existing know-how of Git and CI/CD to keep your code, data and model connected at all times. DVC versions data and models right in Git repositories, and CML orchestrates resources in the cloud or Kubernetes.

Automation of your ML process

Iterate faster, and lower risks by transitioning to an intuitive no-code interface. Bridge the gap between data scientists, software engineers and managers, once and for all.

Mature ML teams reuse their code over and over again while tuning data and params. Iterate faster by transitioning to a no-code environment - use a visual UI to make and deploy changes instead of manually updating code each time.

On the roadmap

Keep an eye out for new features around model and data registries for your ML data to facilitate data discoverability and security.

Plans and pricing

Free

Free for small teams up to 2 members

Unlimited repositories
Integration with popular Git providers
Integration with on-premises GitLab
Sharing projects
Running experiments
Plots visualization
Data-centric comparison of experiments
Integration with common cloud providers
Granular Access Control
Authentication via popular Git providers and emails
Model registry NEW

Basic

$40 per team member monthly

Collaboration on Machine Learning projects for teams of any size

Everything in Free plan, plus:

Unlimited collaborators

Most suitable for teams

Teams

$99 per team member monthly

Basic plan with added MLOps services and support

Everything in Basic plan, plus:

Priority support
Onboarding
Customer success
Quarterly review of MLOps goals

Enterprise

For a large teams collaboration with security requirements

Everything in Teams plan, plus:

Flexible deployment (our VPC, your VPC, on-premises)
Dedicated ML solution architect and professional services

We offer discounts to active DVC/CML teams, nonprofits, and educational institutions for Enterprise plan. Reach out to learn more.

Compare features

	Free	Basic	Teams	Enterprise
Price	$0	$40 per team member monthly	$99 per team member monthly	Custom price *
Team members	Up to 2 per team	Purchased amount	Purchased amount	Purchased amount
Hosting and installation	Free	Basic	Teams	Enterprise
Integration with GitLab.com, GitHub.com, Bitbucket.org
Integration with on-premises GitLab
Integration with on-premises GitHub and Bitbucket (requires on-premises Studio installation)
Flexible deployment (our VPC, your VPC, on-premises)
Features	Free	Basic	Teams	Enterprise
Number of Git repositories that can be connected	Unlimited	Unlimited	Unlimited	Unlimited
Sharing projects with teams/public
Running experiments
Plots visualisation
Data-centric comparison of experiments
Integration with common cloud providers including AWS, GCP, Azure and Kubernetes
Model RegistryNEW
Upcoming
Data Catalog for structured (csv, parquet) and unstructured (images, audio) datasoon
Security	Free	Basic	Teams	Enterprise
Granular Access Control (Read, Write, Admin)
Authentication via GitHub, GitLab and Bitbucket and email
Support	Free	Basic	Teams	Enterprise
Community support
Email support
Priority support
Dedicated ML solution architect and professional services			Limited