Why Polyaxon

Polyaxon brings an A.I layer to your organization’s infrastructure to rapidly develop and deliver models that drive business impact.

For Data Scientists

Use the tools you love on a scalable infrastructure that automatically tracks your work.

Painless experimentation process with minimal infrastructure work

Polyaxon enables your data scientists to easily develop and manage experiments. All your workflow is managed by smart containers and advanced scheduling without being a devops expert.

Unlimited choices of tools and frameworks

Polyaxon is language and framework agnostic, you can work with popular libraries and frameworks, such as R, Python, SAS, Jupyter, RStudio, Tensorflow, and H2O. Or build instantantly custom environment based on new data science tools and packages you’d like.

Caching and isolation

Environments are cached and safely sandboxed to give you and your teammates complete isolation.

One place to build, validate, deliver, and monitor models

The Reproducibility engine automatically tracks all experiments, so you never lose work and can always reproduce results. Every step is saved and can be audited any time, which allows your data scientists to find, understand, build on, and collaborate back to a single knowledge base.

Full ownership of model development and deployment

Reduce time spent on ideation, every data scientist should be able to develop, deploy, and validate models with minimal friction.

Documentation and support

Very well Documented platform, with technical reference docs, getting started guides, learning resources, guides, tutorials, changelogs, and more. In addition, Polyaxon offers a variety of support options for customized assistance.
For Team Leads

Help your team build and deliver models faster by using one single platform to manage the complete life cycle.

Faster iteration

Gain more productivity by maximising your cluster’s resources and robust schdeduling, parallel jobs, and distributed experiments.

Shorter life cycle

Shorten time to delivery by giving your team members full owner ship of their experiments.

Risk management

Use the built-in auto-documentation engine to remove risk and create a searchable knowledge base, and avoid laptop and scattered scripts oriented development.

knowledge distribution

Faster onboarding of new team members with customizable build environment, documented and searchable knowledge base, any new hire can quickly pick up where others left off, with each project's artifacts and history.

Remove duplication

Remove effort duplication and wasted time and engage your whole organization by creating a virtuous cycle of collaboration, feedback, experimentation, and validation.

Better insights

Better decision making and prioritization of ideas and hypothesis.

Better visibility

Centralised dashboard to gain a better visibility on project development and experiments’ metrics.

Team collaboration

A single system for your entire experimentation process, with collaboration tools, shared projects, workspaces, and processes.
For Architects

Establish a secure, scalable, and centralized practices with full compliance, governance, and transparency.

Deploy once and scale when needed

Deploy polyaxon to your platform of choice, and provision resources as needed.

Control your data center cost, and optimize resources allocation with minimal intervention

Elastically provision resources in a cloud or across on-premises hardware, and let your datascientists alter scheduling through a simple interface.

stronger auditing

Manage access to resources per user/team/project.

Stronger governance

Enable full compliance and auditing with complete history of logs, access, and assets.

Support

A range of support options are available to help you troubleshoot issues and ensure your apps run smoothly. Premium support and Polyaxon EE offer faster escalation for critical issues.
For Executives

Improve your return on investment and align your teams' technical skills with business objectives

Improve your return on investment, and transform your organization into data and model driven organization.

Optimize your data scientists time on things they know how to do instead of devops work.

Knowledge distribution

Remove duplication and enable knowledge distribution in your team.

Enable innovation

Leverage latest innovation to drive better metrics and performance.

Optimize your compute resources

Enable flexible and elastic infrastructure and measure costs.

Get better insights on model development and measure your time to market

Enable a virtuous experimentation life cycle by giving data driven feedback based on a centralised dashboard.

Reduce regulatory risk

Introduce rigorous yet auditable workflow through best practices.

Reduce operational risk

Reduce risk through auto-documentation and organized tracking, and remove dependence on key-people.

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